Hello all
I am kinda new in MATLAB/Simulink，and learning the multi-object tracking task based on simulink by Track Closely Spaced Targets Under Ambiguity in Simulink. I want to finish image tracking task. I already have the target detection result based on YOLO. When I was writing based on the HelperDataLogReader class in the example, an assertion failure occurred. But I have looked up a lot of relevant materials but can’t solve it, and I hope someone can help me. Here is my code and the target detection result of YOLO, thank you so much！
classdef (StrictDefaults)HelperDataReader < …
matlabshared.tracking.internal.SimulinkBusUtilities

% This is a helper block for example purposes and may be removed or
% modified in the future.
%
% Copyright 2019 The MathWorks, Inc.

properties(Constant, Access=protected)
pBusPrefix = ‘BusDataLogReader’
end
properties(Access = public, Nontunable)
Data
end

properties(Nontunable)
Frame = fusionCoordinateFrameType.Rectangular
end

properties(Access = private)
%pCurrentIndex
pCurrentIndex = 0

%pMaxIndex Saved the maximum time step index in the data file
pMaxIndex

end

methods
function obj = HelperDataReader(varargin)
% Constructor
setProperties(obj,nargin,varargin{:});
end
end

methods(Access=protected)

function [out, argsToBus] = defaultOutput(obj)
objAtt = struct(‘Score’,double(1));
out = struct(‘Time’,double(1),…
‘Measurement’,double(zeros(1, 4)),…
‘MeasurementNoise’,double(zeros(4)),…
‘SensorIndex’,double(0),…
‘ObjectClassID’,double(0),…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,objAtt);
argsToBus = {out};
end

% Currently only support simulink environment, so nothing to do
% here
function y = sendToBus(~,x,varargin)
[newx,num] = objDet2Struct(x);
y = struct(‘Detections’,newx,’NumDetections’,num);
end

function [det, time] = stepImpl(obj)
if ~obj.isEndOfData()
obj.pCurrentIndex = obj.pCurrentIndex + 1;
end
newDet = obj.Data.detections{obj.pCurrentIndex};
det = sendToBus(obj,newDet);
time = newDet(1).Time;
end

function setupImpl(obj, varargin)
obj.Data = load(‘PedestrianTrackingYOLODetections.mat’);
obj.pMaxIndex =numel(obj.Data.detections);
end
function loadObjectImpl(obj,s,wasLocked)
% Set properties in object obj to values in structure s

% Set public properties and states
loadObjectImpl@matlab.System(obj,s,wasLocked);
end

function status = isEndOfData(obj)
% Return true if end of data has been reached
status = (obj.pCurrentIndex == obj.pMaxIndex);
end

function s = saveObjectImpl(obj)
% Set properties in structure s to values in object obj

% Set public properties and states
s = saveObjectImpl@matlab.System(obj);
end

% function varargout = getOutputDataTypeImpl(obj)
% varargout{1} = getOutputDataTypeImpl@matlabshared.tracking.internal.SimulinkBusUtilities(obj);
% varargout{2} = "double";
% end

function str = getIconImpl(~)
str = sprintf(‘HelpernDataLognReader’);
end

function varargout = getOutputNamesImpl(~)
varargout{1} = sprintf(‘Detections’);
varargout{2} = sprintf(‘Time’);
end
function varargout = getInputNamesImpl(~)
varargout{1} = sprintf(‘In’);
end
function [out1,out2] = isOutputFixedSizeImpl(~)
out1 = true;
out2 = true;
end
function [out1,out2] = getOutputSizeImpl(~)
out1 = [1 1];
out2 = [1 1];
end

function [out1,out2] = isOutputComplexImpl(~)
out1 = false;
out2 = false;
end
end
methods(Static, Hidden)
function flag = isAllowedInSystemBlock
flag = true;
end

end
methods(Static, Access=protected)
function header = getHeaderImpl
% Define header panel for System block dialog
header = matlab.system.display.Header(…
‘Title’, ‘DataLogReader’, …
‘Text’, getHeaderText());
end
function simMode = getSimulateUsingImpl
% Return only allowed simulation mode in System block dialog
simMode = ‘Interpreted execution’;
end
function flag = showSimulateUsingImpl
% Return false if simulation mode hidden in System block dialog
flag = false;
end
end

end
function str = getHeaderText
str = sprintf(‘The DataLog reader reads a struct file and it outputs the detection and time.’);
end
function [yDet,num] = objDet2Struct(det)
num = numel(det);
for i =1:num
yDet(i) = struct(‘Time’,det(i).Time,…
‘Measurement’,det(i).Measurement,…
‘MeasurementNoise’,det(i).MeasurementNoise,…
‘SensorIndex’,det(i).SensorIndex,…
‘ObjectClassID’,det(i).ObjectClassID,…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,det(i).ObjectAttributes); %#ok<AGROW>
end
endHello all
I am kinda new in MATLAB/Simulink，and learning the multi-object tracking task based on simulink by Track Closely Spaced Targets Under Ambiguity in Simulink. I want to finish image tracking task. I already have the target detection result based on YOLO. When I was writing based on the HelperDataLogReader class in the example, an assertion failure occurred. But I have looked up a lot of relevant materials but can’t solve it, and I hope someone can help me. Here is my code and the target detection result of YOLO, thank you so much！
classdef (StrictDefaults)HelperDataReader < …
matlabshared.tracking.internal.SimulinkBusUtilities

% This is a helper block for example purposes and may be removed or
% modified in the future.
%
% Copyright 2019 The MathWorks, Inc.

properties(Constant, Access=protected)
pBusPrefix = ‘BusDataLogReader’
end
properties(Access = public, Nontunable)
Data
end

properties(Nontunable)
Frame = fusionCoordinateFrameType.Rectangular
end

properties(Access = private)
%pCurrentIndex
pCurrentIndex = 0

%pMaxIndex Saved the maximum time step index in the data file
pMaxIndex

end

methods
function obj = HelperDataReader(varargin)
% Constructor
setProperties(obj,nargin,varargin{:});
end
end

methods(Access=protected)

function [out, argsToBus] = defaultOutput(obj)
objAtt = struct(‘Score’,double(1));
out = struct(‘Time’,double(1),…
‘Measurement’,double(zeros(1, 4)),…
‘MeasurementNoise’,double(zeros(4)),…
‘SensorIndex’,double(0),…
‘ObjectClassID’,double(0),…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,objAtt);
argsToBus = {out};
end

% Currently only support simulink environment, so nothing to do
% here
function y = sendToBus(~,x,varargin)
[newx,num] = objDet2Struct(x);
y = struct(‘Detections’,newx,’NumDetections’,num);
end

function [det, time] = stepImpl(obj)
if ~obj.isEndOfData()
obj.pCurrentIndex = obj.pCurrentIndex + 1;
end
newDet = obj.Data.detections{obj.pCurrentIndex};
det = sendToBus(obj,newDet);
time = newDet(1).Time;
end

function setupImpl(obj, varargin)
obj.Data = load(‘PedestrianTrackingYOLODetections.mat’);
obj.pMaxIndex =numel(obj.Data.detections);
end
function loadObjectImpl(obj,s,wasLocked)
% Set properties in object obj to values in structure s

% Set public properties and states
loadObjectImpl@matlab.System(obj,s,wasLocked);
end

function status = isEndOfData(obj)
% Return true if end of data has been reached
status = (obj.pCurrentIndex == obj.pMaxIndex);
end

function s = saveObjectImpl(obj)
% Set properties in structure s to values in object obj

% Set public properties and states
s = saveObjectImpl@matlab.System(obj);
end

% function varargout = getOutputDataTypeImpl(obj)
% varargout{1} = getOutputDataTypeImpl@matlabshared.tracking.internal.SimulinkBusUtilities(obj);
% varargout{2} = "double";
% end

function str = getIconImpl(~)
str = sprintf(‘HelpernDataLognReader’);
end

function varargout = getOutputNamesImpl(~)
varargout{1} = sprintf(‘Detections’);
varargout{2} = sprintf(‘Time’);
end
function varargout = getInputNamesImpl(~)
varargout{1} = sprintf(‘In’);
end
function [out1,out2] = isOutputFixedSizeImpl(~)
out1 = true;
out2 = true;
end
function [out1,out2] = getOutputSizeImpl(~)
out1 = [1 1];
out2 = [1 1];
end

function [out1,out2] = isOutputComplexImpl(~)
out1 = false;
out2 = false;
end
end
methods(Static, Hidden)
function flag = isAllowedInSystemBlock
flag = true;
end

end
methods(Static, Access=protected)
function header = getHeaderImpl
% Define header panel for System block dialog
header = matlab.system.display.Header(…
‘Title’, ‘DataLogReader’, …
‘Text’, getHeaderText());
end
function simMode = getSimulateUsingImpl
% Return only allowed simulation mode in System block dialog
simMode = ‘Interpreted execution’;
end
function flag = showSimulateUsingImpl
% Return false if simulation mode hidden in System block dialog
flag = false;
end
end

end
function str = getHeaderText
str = sprintf(‘The DataLog reader reads a struct file and it outputs the detection and time.’);
end
function [yDet,num] = objDet2Struct(det)
num = numel(det);
for i =1:num
yDet(i) = struct(‘Time’,det(i).Time,…
‘Measurement’,det(i).Measurement,…
‘MeasurementNoise’,det(i).MeasurementNoise,…
‘SensorIndex’,det(i).SensorIndex,…
‘ObjectClassID’,det(i).ObjectClassID,…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,det(i).ObjectAttributes); %#ok<AGROW>
end
end Hello all
I am kinda new in MATLAB/Simulink，and learning the multi-object tracking task based on simulink by Track Closely Spaced Targets Under Ambiguity in Simulink. I want to finish image tracking task. I already have the target detection result based on YOLO. When I was writing based on the HelperDataLogReader class in the example, an assertion failure occurred. But I have looked up a lot of relevant materials but can’t solve it, and I hope someone can help me. Here is my code and the target detection result of YOLO, thank you so much！
classdef (StrictDefaults)HelperDataReader < …
matlabshared.tracking.internal.SimulinkBusUtilities

% This is a helper block for example purposes and may be removed or
% modified in the future.
%
% Copyright 2019 The MathWorks, Inc.

properties(Constant, Access=protected)
pBusPrefix = ‘BusDataLogReader’
end
properties(Access = public, Nontunable)
Data
end

properties(Nontunable)
Frame = fusionCoordinateFrameType.Rectangular
end

properties(Access = private)
%pCurrentIndex
pCurrentIndex = 0

%pMaxIndex Saved the maximum time step index in the data file
pMaxIndex

end

methods
function obj = HelperDataReader(varargin)
% Constructor
setProperties(obj,nargin,varargin{:});
end
end

methods(Access=protected)

function [out, argsToBus] = defaultOutput(obj)
objAtt = struct(‘Score’,double(1));
out = struct(‘Time’,double(1),…
‘Measurement’,double(zeros(1, 4)),…
‘MeasurementNoise’,double(zeros(4)),…
‘SensorIndex’,double(0),…
‘ObjectClassID’,double(0),…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,objAtt);
argsToBus = {out};
end

% Currently only support simulink environment, so nothing to do
% here
function y = sendToBus(~,x,varargin)
[newx,num] = objDet2Struct(x);
y = struct(‘Detections’,newx,’NumDetections’,num);
end

function [det, time] = stepImpl(obj)
if ~obj.isEndOfData()
obj.pCurrentIndex = obj.pCurrentIndex + 1;
end
newDet = obj.Data.detections{obj.pCurrentIndex};
det = sendToBus(obj,newDet);
time = newDet(1).Time;
end

function setupImpl(obj, varargin)
obj.Data = load(‘PedestrianTrackingYOLODetections.mat’);
obj.pMaxIndex =numel(obj.Data.detections);
end
function loadObjectImpl(obj,s,wasLocked)
% Set properties in object obj to values in structure s

% Set public properties and states
loadObjectImpl@matlab.System(obj,s,wasLocked);
end

function status = isEndOfData(obj)
% Return true if end of data has been reached
status = (obj.pCurrentIndex == obj.pMaxIndex);
end

function s = saveObjectImpl(obj)
% Set properties in structure s to values in object obj

% Set public properties and states
s = saveObjectImpl@matlab.System(obj);
end

% function varargout = getOutputDataTypeImpl(obj)
% varargout{1} = getOutputDataTypeImpl@matlabshared.tracking.internal.SimulinkBusUtilities(obj);
% varargout{2} = "double";
% end

function str = getIconImpl(~)
str = sprintf(‘HelpernDataLognReader’);
end

function varargout = getOutputNamesImpl(~)
varargout{1} = sprintf(‘Detections’);
varargout{2} = sprintf(‘Time’);
end
function varargout = getInputNamesImpl(~)
varargout{1} = sprintf(‘In’);
end
function [out1,out2] = isOutputFixedSizeImpl(~)
out1 = true;
out2 = true;
end
function [out1,out2] = getOutputSizeImpl(~)
out1 = [1 1];
out2 = [1 1];
end

function [out1,out2] = isOutputComplexImpl(~)
out1 = false;
out2 = false;
end
end
methods(Static, Hidden)
function flag = isAllowedInSystemBlock
flag = true;
end

end
methods(Static, Access=protected)
function header = getHeaderImpl
% Define header panel for System block dialog
header = matlab.system.display.Header(…
‘Title’, ‘DataLogReader’, …
‘Text’, getHeaderText());
end
function simMode = getSimulateUsingImpl
% Return only allowed simulation mode in System block dialog
simMode = ‘Interpreted execution’;
end
function flag = showSimulateUsingImpl
% Return false if simulation mode hidden in System block dialog
flag = false;
end
end

end
function str = getHeaderText
str = sprintf(‘The DataLog reader reads a struct file and it outputs the detection and time.’);
end
function [yDet,num] = objDet2Struct(det)
num = numel(det);
for i =1:num
yDet(i) = struct(‘Time’,det(i).Time,…
‘Measurement’,det(i).Measurement,…
‘MeasurementNoise’,det(i).MeasurementNoise,…
‘SensorIndex’,det(i).SensorIndex,…
‘ObjectClassID’,det(i).ObjectClassID,…
‘ObjectClassParameters’, [],…
‘ObjectAttributes’,det(i).ObjectAttributes); %#ok<AGROW>
end
end multi-object tracking, sensor fusion and tracking toolbox, system object MATLAB Answers — New Questions

​

I have the following data:
Ax, Ay, Az (m/s^2) – update rate 10 Hz
Gx, Gy, Gz (rad/s) – update rate 10 Hz
GPS LLA (deg deg meters) – update rate 2 Hz
Roll, Pitch, Yaw (degrees) update rate 10 Hz
I want to develop a GNSS aided INS.
I am following the example given below:
https://www.mathworks.com/help/nav/ug/imu-and-gps-fusion-for-inertial-navigation.html
trajOrient = trajData.Orientation;
I got this using the below code:
%%
clear all;
close all;
clc;

%%
%Load sensor data
load IMUData.mat IMUData;

accelerometerReadings = IMUData(:, 2:4);
gyroscopeReadings = IMUData(:, 5:7);

%% Sampling Rate
imuFs = 10; %Hz
decim = 1;
fuse = imufilter(‘SampleRate’,imuFs,’DecimationFactor’,decim, ‘ReferenceFrame’, ‘ENU’,’AccelerometerNoise’,1e-6, ‘GyroscopeDriftNoise’,1e-6);

%%
OrientationData = fuse(accelerometerReadings,gyroscopeReadings);
trajVel = trajData.Velocity;
How do I get this data?
trajPos = trajData.Position;
How do I get this data?
trajAcc = trajData.Acceleration;
accelerometerReadings = IMUData(:, 2:4);
trajAngVel = trajData.AngularVelocity;
gyroscopeReadings = IMUData(:, 5:7);

Also, I do not have magnetometer. I have to do it using acc-gyro only.

initstate = [1-4 % Orientation as a quaternion
5-7 % Position (NED) %but my frame is in NEU maybe
8-10 % Velocity (NED)
11-13 % Delta Angle Bias (XYZ)
14-16 % Delta Velocity Bias (XYZ)
17-19; % Geomagnetic Field Vector (NED)
20-22] % Magnetometer Bias (XYZ)

How can I proceed with this?I have the following data:
Ax, Ay, Az (m/s^2) – update rate 10 Hz
Gx, Gy, Gz (rad/s) – update rate 10 Hz
GPS LLA (deg deg meters) – update rate 2 Hz
Roll, Pitch, Yaw (degrees) update rate 10 Hz
I want to develop a GNSS aided INS.
I am following the example given below:
https://www.mathworks.com/help/nav/ug/imu-and-gps-fusion-for-inertial-navigation.html
trajOrient = trajData.Orientation;
I got this using the below code:
%%
clear all;
close all;
clc;

%%
%Load sensor data
load IMUData.mat IMUData;

accelerometerReadings = IMUData(:, 2:4);
gyroscopeReadings = IMUData(:, 5:7);

%% Sampling Rate
imuFs = 10; %Hz
decim = 1;
fuse = imufilter(‘SampleRate’,imuFs,’DecimationFactor’,decim, ‘ReferenceFrame’, ‘ENU’,’AccelerometerNoise’,1e-6, ‘GyroscopeDriftNoise’,1e-6);

%%
OrientationData = fuse(accelerometerReadings,gyroscopeReadings);
trajVel = trajData.Velocity;
How do I get this data?
trajPos = trajData.Position;
How do I get this data?
trajAcc = trajData.Acceleration;
accelerometerReadings = IMUData(:, 2:4);
trajAngVel = trajData.AngularVelocity;
gyroscopeReadings = IMUData(:, 5:7);

Also, I do not have magnetometer. I have to do it using acc-gyro only.

initstate = [1-4 % Orientation as a quaternion
5-7 % Position (NED) %but my frame is in NEU maybe
8-10 % Velocity (NED)
11-13 % Delta Angle Bias (XYZ)
14-16 % Delta Velocity Bias (XYZ)
17-19; % Geomagnetic Field Vector (NED)
20-22] % Magnetometer Bias (XYZ)

How can I proceed with this? I have the following data:
Ax, Ay, Az (m/s^2) – update rate 10 Hz
Gx, Gy, Gz (rad/s) – update rate 10 Hz
GPS LLA (deg deg meters) – update rate 2 Hz
Roll, Pitch, Yaw (degrees) update rate 10 Hz
I want to develop a GNSS aided INS.
I am following the example given below:
https://www.mathworks.com/help/nav/ug/imu-and-gps-fusion-for-inertial-navigation.html
trajOrient = trajData.Orientation;
I got this using the below code:
%%
clear all;
close all;
clc;

%%
%Load sensor data
load IMUData.mat IMUData;

accelerometerReadings = IMUData(:, 2:4);
gyroscopeReadings = IMUData(:, 5:7);

%% Sampling Rate
imuFs = 10; %Hz
decim = 1;
fuse = imufilter(‘SampleRate’,imuFs,’DecimationFactor’,decim, ‘ReferenceFrame’, ‘ENU’,’AccelerometerNoise’,1e-6, ‘GyroscopeDriftNoise’,1e-6);

%%
OrientationData = fuse(accelerometerReadings,gyroscopeReadings);
trajVel = trajData.Velocity;
How do I get this data?
trajPos = trajData.Position;
How do I get this data?
trajAcc = trajData.Acceleration;
accelerometerReadings = IMUData(:, 2:4);
trajAngVel = trajData.AngularVelocity;
gyroscopeReadings = IMUData(:, 5:7);

Also, I do not have magnetometer. I have to do it using acc-gyro only.

initstate = [1-4 % Orientation as a quaternion
5-7 % Position (NED) %but my frame is in NEU maybe
8-10 % Velocity (NED)
11-13 % Delta Angle Bias (XYZ)
14-16 % Delta Velocity Bias (XYZ)
17-19; % Geomagnetic Field Vector (NED)
20-22] % Magnetometer Bias (XYZ)

How can I proceed with this? inertial navigation, gps, localization, ekf MATLAB Answers — New Questions

​

I am running a circuit simulation in MATLAB that has a 4 pin SIC FET. These pins include Drain, Gate and two Source pins.
The library of the part number is available from manufacturer website in .LIB and include subcircuit model of the 4 pin FET component.
I am basically using this link below to generate thae MATLAB model for this part using lookup table generation approach from subcircuit model:
https://www.mathworks.com/help/sps/ref/ee.spice.semiconductorsubcircuit2lookup.html
I am getting an error related to SIMetrix as attachement. Does matlab use SIMetrix engin for this model conversion? How I can fix this error? I have already installed SIMetrix at the mentioned directory in attachement.I am running a circuit simulation in MATLAB that has a 4 pin SIC FET. These pins include Drain, Gate and two Source pins.
The library of the part number is available from manufacturer website in .LIB and include subcircuit model of the 4 pin FET component.
I am basically using this link below to generate thae MATLAB model for this part using lookup table generation approach from subcircuit model:
https://www.mathworks.com/help/sps/ref/ee.spice.semiconductorsubcircuit2lookup.html
I am getting an error related to SIMetrix as attachement. Does matlab use SIMetrix engin for this model conversion? How I can fix this error? I have already installed SIMetrix at the mentioned directory in attachement. I am running a circuit simulation in MATLAB that has a 4 pin SIC FET. These pins include Drain, Gate and two Source pins.
The library of the part number is available from manufacturer website in .LIB and include subcircuit model of the 4 pin FET component.
I am basically using this link below to generate thae MATLAB model for this part using lookup table generation approach from subcircuit model:
https://www.mathworks.com/help/sps/ref/ee.spice.semiconductorsubcircuit2lookup.html
I am getting an error related to SIMetrix as attachement. Does matlab use SIMetrix engin for this model conversion? How I can fix this error? I have already installed SIMetrix at the mentioned directory in attachement. circuit model, spice, sic fet, 4 pin fet MATLAB Answers — New Questions

​

Hi Community,
I am building a current controller for a three phase inverter in the dq frame. I have two models. Both are attached here.
Model 1 is built with Simscape Specialised Pwer systems library components &
Model 2 has components from Simscape electrical.
Expected Results – Measured Id and Iq should follow the setpoint/references provided for each respectively. As there is PID control involved there will be some overshoot, rise time etc as expected, but eventually steady state values should converge to the reference.
With all the parameters and controller design same (to the best of my knowledge) I see desired results with Model 1 but not with Model 2. Any ideas why this could be happening?
Model 1

Model 1 results

Model 2

Model 2 results

This result not does not follow the setpoint but also becomes unstable. The PID parameters are the same but could there be a need for different tuning? If so why, since the input output ranges should be similar as all the other parameters are the same.

Due credit for Model 1
"Syed Abdul Rahman Kashif (2025). Grid Tied Inverter with Current Controller (https://www.mathworks.com/matlabcentral/fileexchange/130854-grid-tied-inverter-with-current-controller), MATLAB Central File Exchange. Retrieved January 31, 2025."Hi Community,
I am building a current controller for a three phase inverter in the dq frame. I have two models. Both are attached here.
Model 1 is built with Simscape Specialised Pwer systems library components &
Model 2 has components from Simscape electrical.
Expected Results – Measured Id and Iq should follow the setpoint/references provided for each respectively. As there is PID control involved there will be some overshoot, rise time etc as expected, but eventually steady state values should converge to the reference.
With all the parameters and controller design same (to the best of my knowledge) I see desired results with Model 1 but not with Model 2. Any ideas why this could be happening?
Model 1

Model 1 results

Model 2

Model 2 results

This result not does not follow the setpoint but also becomes unstable. The PID parameters are the same but could there be a need for different tuning? If so why, since the input output ranges should be similar as all the other parameters are the same.

Due credit for Model 1
"Syed Abdul Rahman Kashif (2025). Grid Tied Inverter with Current Controller (https://www.mathworks.com/matlabcentral/fileexchange/130854-grid-tied-inverter-with-current-controller), MATLAB Central File Exchange. Retrieved January 31, 2025." Hi Community,
I am building a current controller for a three phase inverter in the dq frame. I have two models. Both are attached here.
Model 1 is built with Simscape Specialised Pwer systems library components &
Model 2 has components from Simscape electrical.
Expected Results – Measured Id and Iq should follow the setpoint/references provided for each respectively. As there is PID control involved there will be some overshoot, rise time etc as expected, but eventually steady state values should converge to the reference.
With all the parameters and controller design same (to the best of my knowledge) I see desired results with Model 1 but not with Model 2. Any ideas why this could be happening?
Model 1

Model 1 results

Model 2

Model 2 results

This result not does not follow the setpoint but also becomes unstable. The PID parameters are the same but could there be a need for different tuning? If so why, since the input output ranges should be similar as all the other parameters are the same.

Due credit for Model 1
"Syed Abdul Rahman Kashif (2025). Grid Tied Inverter with Current Controller (https://www.mathworks.com/matlabcentral/fileexchange/130854-grid-tied-inverter-with-current-controller), MATLAB Central File Exchange. Retrieved January 31, 2025." dq control, current control, pq control, three phase inverter, mmc, simscape sps, simscape electrical MATLAB Answers — New Questions

​

No equations for the modelling of the transformer with three windings are provided in the documentation. This would be however very helpful for an exact current control design of a grid converter. Is there any documentation available?No equations for the modelling of the transformer with three windings are provided in the documentation. This would be however very helpful for an exact current control design of a grid converter. Is there any documentation available? No equations for the modelling of the transformer with three windings are provided in the documentation. This would be however very helpful for an exact current control design of a grid converter. Is there any documentation available? transformer three windings MATLAB Answers — New Questions

​

我正在尝试使用rtwbuildmatsim脚本导出tutorial_matsim_start_spr_dmp_01.mdl的Simulink模型。
I am trying to export a Simulink model of tutorial_matsim_start_spr_dmp_01.mdl using the rtwbuildmatsim script.

之前在Simulink的Simulation菜单下的Model Configuration Parameters中选择的导出的目标文件类型为matsim.tlc。
The export target file type selected in Model Configuration Parameters under the Simulation menu of Simulink is matsim.tlc.

在执行脚本的过程中，发生了报错：unable to locate template makefile: matsim_lcc64.tmf
An error occurred while executing the script: unable to locate template makefile: matsim_lcc64.tmf

我从报错上判断问题就是MATLAB没有找到模板文件matsim_lcc64.tmf。然而我搜索了MATLAB的所有文件均未找到该模板文件。我搜索过该文件的版本包括MATLAB 2021b20219b2015a。我选择的编译器为MinGW 6.3。
I judged from the error that the problem was that MATLAB did not find the template file matsim_lcc64.tmf. However, I searched all the files in MATLAB and could not find the template file. I have searched for versions of this file including MATLAB 2021b20219b2015a. The compiler I chose is MinGW 6.3.
感谢您的帮助！
Thank you for your help！
附：报错全部内容：
Attached: All contents of the error:
### Generating code and artifacts to ‘Model specific’ folder structure ### Generating code into build folder: E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw 警告: Model ‘tutorial_matsim_start_spr_dmp_01’ is using a default value of 0.2 for maximum step size. You can disable this diagnostic by setting Automatic solver parameter selection to ‘none’ ### Invoking Target Language Compiler on tutorial_matsim_start_spr_dmp_01.rtw ### Using System Target File: E:SOFTMATLABR2019brtwcrtwsfcnrtwsfcn.tlc ### Loading TLC function libraries …. ### Initial pass through model to cache user defined code . ### Caching model source code …………………. ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_types.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sf.h ### Writing header file rtwtypes.h . ### Writing header file multiword_types.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf.c ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_private.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sid.h ### Writing header file tutorial_matsim_start_spr_dmp_01_mid.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf_data.c ### Writing header file rtGetNaN.h . ### Writing source file rtGetNaN.c ### Writing header file rt_nonfinite.h ### Writing source file rt_nonfinite.c ### Writing header file rt_defines.h ### Writing header file rtGetInf.h ### Writing source file rtGetInf.c . ### TLC code generation complete. ### Using toolchain: MinGW64 | gmake (64-bit Windows) ### Creating ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtwtutorial_matsim_start_spr_dmp_01.mk’ … ### Building ‘tutorial_matsim_start_spr_dmp_01_sf’: "E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>cd . E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>if "" == "" ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all ) else ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk ) "### Successfully generated all binary outputs." E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>exit 0 mex -f E:SOFTMATLABR2019bbinwin64mexoptsmingw64.xml -R2018a -outdir .. ‘CFLAGS=$CFLAGS -Wno-overlength-strings -pedantic -Wno-long-long -Wno-declaration-after-statement -fwrapv’ -DMODEL=tutorial_matsim_start_spr_dmp_01 -DNUMST=1 -DNCSTATES=0 -DHAVESTDIO -DCLASSIC_INTERFACE=1 -DALLOCATIONFCN=0 -DTID01EQ=0 -DONESTEPFCN=0 -DTERMFCN=1 -DMULTI_INSTANCE_CODE=0 -DINTEGER_CODE=0 COPTIMFLAGS=-O0 -I.. -I..tutorial_matsim_start_spr_dmp_01_sfcn_rtw -IE:SOFTMATLABR2019bexterninclude -IE:SOFTMATLABR2019bsimulinkinclude -IE:SOFTMATLABR2019brtwcsrc tutorial_matsim_start_spr_dmp_01_sf.c rtGetInf.c rtGetNaN.c tutorial_matsim_start_spr_dmp_01_sf_data.c -LE:SOFTMATLABR2019bexternlibwin64mingw64 -lut -lfixedpoint ### Created mex file: ..tutorial_matsim_start_spr_dmp_01_sf.mexw64 ### Simulink cache artifacts for ‘tutorial_matsim_start_spr_dmp_01’ were created in ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01.slxc’. 错误使用 getTMF Unable to locate template makefile: matsim_lcc64.tmf 出错 rtwprivate (line 16) [varargout{1:nargout}] = feval(function_name, varargin{1:end}); 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.ModelCompInfo/createModelCompInfoPrivate 出错 coder.internal.ModelCompInfo.createModelCompInfo 出错 slbuild_private 出错 sl (line 15) [varargout{1:nargout}]=feval(varargin{:}); 出错 slbuild (line 98) sl(‘slbuild_private’, mdl, target, varargin{2:end}); 出错 rtwbuild (line 235) slbuild(sys, ‘StandaloneCoderTarget’, … 出错 rtwbuildmatsim (line 70) rtwbuild(p.Results.model); – Show complete stack trace Displaying stack trace: Error using getTMF • In getTMF • In rtwprivate (line 16) • In coder.internal.getMexCompilerForModel • In coder.internal.getMexCompilerForModel • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfoPrivate • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfo • In slbuild_private • In sl (line 15) • In slbuild (line 98) • In rtwbuild (line 235) • In rtwbuildmatsim (line 70)我正在尝试使用rtwbuildmatsim脚本导出tutorial_matsim_start_spr_dmp_01.mdl的Simulink模型。
I am trying to export a Simulink model of tutorial_matsim_start_spr_dmp_01.mdl using the rtwbuildmatsim script.

之前在Simulink的Simulation菜单下的Model Configuration Parameters中选择的导出的目标文件类型为matsim.tlc。
The export target file type selected in Model Configuration Parameters under the Simulation menu of Simulink is matsim.tlc.

在执行脚本的过程中，发生了报错：unable to locate template makefile: matsim_lcc64.tmf
An error occurred while executing the script: unable to locate template makefile: matsim_lcc64.tmf

我从报错上判断问题就是MATLAB没有找到模板文件matsim_lcc64.tmf。然而我搜索了MATLAB的所有文件均未找到该模板文件。我搜索过该文件的版本包括MATLAB 2021b20219b2015a。我选择的编译器为MinGW 6.3。
I judged from the error that the problem was that MATLAB did not find the template file matsim_lcc64.tmf. However, I searched all the files in MATLAB and could not find the template file. I have searched for versions of this file including MATLAB 2021b20219b2015a. The compiler I chose is MinGW 6.3.
感谢您的帮助！
Thank you for your help！
附：报错全部内容：
Attached: All contents of the error:
### Generating code and artifacts to ‘Model specific’ folder structure ### Generating code into build folder: E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw 警告: Model ‘tutorial_matsim_start_spr_dmp_01’ is using a default value of 0.2 for maximum step size. You can disable this diagnostic by setting Automatic solver parameter selection to ‘none’ ### Invoking Target Language Compiler on tutorial_matsim_start_spr_dmp_01.rtw ### Using System Target File: E:SOFTMATLABR2019brtwcrtwsfcnrtwsfcn.tlc ### Loading TLC function libraries …. ### Initial pass through model to cache user defined code . ### Caching model source code …………………. ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_types.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sf.h ### Writing header file rtwtypes.h . ### Writing header file multiword_types.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf.c ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_private.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sid.h ### Writing header file tutorial_matsim_start_spr_dmp_01_mid.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf_data.c ### Writing header file rtGetNaN.h . ### Writing source file rtGetNaN.c ### Writing header file rt_nonfinite.h ### Writing source file rt_nonfinite.c ### Writing header file rt_defines.h ### Writing header file rtGetInf.h ### Writing source file rtGetInf.c . ### TLC code generation complete. ### Using toolchain: MinGW64 | gmake (64-bit Windows) ### Creating ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtwtutorial_matsim_start_spr_dmp_01.mk’ … ### Building ‘tutorial_matsim_start_spr_dmp_01_sf’: "E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>cd . E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>if "" == "" ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all ) else ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk ) "### Successfully generated all binary outputs." E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>exit 0 mex -f E:SOFTMATLABR2019bbinwin64mexoptsmingw64.xml -R2018a -outdir .. ‘CFLAGS=$CFLAGS -Wno-overlength-strings -pedantic -Wno-long-long -Wno-declaration-after-statement -fwrapv’ -DMODEL=tutorial_matsim_start_spr_dmp_01 -DNUMST=1 -DNCSTATES=0 -DHAVESTDIO -DCLASSIC_INTERFACE=1 -DALLOCATIONFCN=0 -DTID01EQ=0 -DONESTEPFCN=0 -DTERMFCN=1 -DMULTI_INSTANCE_CODE=0 -DINTEGER_CODE=0 COPTIMFLAGS=-O0 -I.. -I..tutorial_matsim_start_spr_dmp_01_sfcn_rtw -IE:SOFTMATLABR2019bexterninclude -IE:SOFTMATLABR2019bsimulinkinclude -IE:SOFTMATLABR2019brtwcsrc tutorial_matsim_start_spr_dmp_01_sf.c rtGetInf.c rtGetNaN.c tutorial_matsim_start_spr_dmp_01_sf_data.c -LE:SOFTMATLABR2019bexternlibwin64mingw64 -lut -lfixedpoint ### Created mex file: ..tutorial_matsim_start_spr_dmp_01_sf.mexw64 ### Simulink cache artifacts for ‘tutorial_matsim_start_spr_dmp_01’ were created in ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01.slxc’. 错误使用 getTMF Unable to locate template makefile: matsim_lcc64.tmf 出错 rtwprivate (line 16) [varargout{1:nargout}] = feval(function_name, varargin{1:end}); 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.ModelCompInfo/createModelCompInfoPrivate 出错 coder.internal.ModelCompInfo.createModelCompInfo 出错 slbuild_private 出错 sl (line 15) [varargout{1:nargout}]=feval(varargin{:}); 出错 slbuild (line 98) sl(‘slbuild_private’, mdl, target, varargin{2:end}); 出错 rtwbuild (line 235) slbuild(sys, ‘StandaloneCoderTarget’, … 出错 rtwbuildmatsim (line 70) rtwbuild(p.Results.model); – Show complete stack trace Displaying stack trace: Error using getTMF • In getTMF • In rtwprivate (line 16) • In coder.internal.getMexCompilerForModel • In coder.internal.getMexCompilerForModel • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfoPrivate • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfo • In slbuild_private • In sl (line 15) • In slbuild (line 98) • In rtwbuild (line 235) • In rtwbuildmatsim (line 70) 我正在尝试使用rtwbuildmatsim脚本导出tutorial_matsim_start_spr_dmp_01.mdl的Simulink模型。
I am trying to export a Simulink model of tutorial_matsim_start_spr_dmp_01.mdl using the rtwbuildmatsim script.

之前在Simulink的Simulation菜单下的Model Configuration Parameters中选择的导出的目标文件类型为matsim.tlc。
The export target file type selected in Model Configuration Parameters under the Simulation menu of Simulink is matsim.tlc.

在执行脚本的过程中，发生了报错：unable to locate template makefile: matsim_lcc64.tmf
An error occurred while executing the script: unable to locate template makefile: matsim_lcc64.tmf

我从报错上判断问题就是MATLAB没有找到模板文件matsim_lcc64.tmf。然而我搜索了MATLAB的所有文件均未找到该模板文件。我搜索过该文件的版本包括MATLAB 2021b20219b2015a。我选择的编译器为MinGW 6.3。
I judged from the error that the problem was that MATLAB did not find the template file matsim_lcc64.tmf. However, I searched all the files in MATLAB and could not find the template file. I have searched for versions of this file including MATLAB 2021b20219b2015a. The compiler I chose is MinGW 6.3.
感谢您的帮助！
Thank you for your help！
附：报错全部内容：
Attached: All contents of the error:
### Generating code and artifacts to ‘Model specific’ folder structure ### Generating code into build folder: E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw 警告: Model ‘tutorial_matsim_start_spr_dmp_01’ is using a default value of 0.2 for maximum step size. You can disable this diagnostic by setting Automatic solver parameter selection to ‘none’ ### Invoking Target Language Compiler on tutorial_matsim_start_spr_dmp_01.rtw ### Using System Target File: E:SOFTMATLABR2019brtwcrtwsfcnrtwsfcn.tlc ### Loading TLC function libraries …. ### Initial pass through model to cache user defined code . ### Caching model source code …………………. ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_types.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sf.h ### Writing header file rtwtypes.h . ### Writing header file multiword_types.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf.c ### Writing header file tutorial_matsim_start_spr_dmp_01_sf_private.h ### Writing header file tutorial_matsim_start_spr_dmp_01_sid.h ### Writing header file tutorial_matsim_start_spr_dmp_01_mid.h ### Writing source file tutorial_matsim_start_spr_dmp_01_sf_data.c ### Writing header file rtGetNaN.h . ### Writing source file rtGetNaN.c ### Writing header file rt_nonfinite.h ### Writing source file rt_nonfinite.c ### Writing header file rt_defines.h ### Writing header file rtGetInf.h ### Writing source file rtGetInf.c . ### TLC code generation complete. ### Using toolchain: MinGW64 | gmake (64-bit Windows) ### Creating ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtwtutorial_matsim_start_spr_dmp_01.mk’ … ### Building ‘tutorial_matsim_start_spr_dmp_01_sf’: "E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>cd . E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>if "" == "" ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk all ) else ("E:SOFTMATLABR2019bbinwin64gmake" -f tutorial_matsim_start_spr_dmp_01.mk ) "### Successfully generated all binary outputs." E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01_sfcn_rtw>exit 0 mex -f E:SOFTMATLABR2019bbinwin64mexoptsmingw64.xml -R2018a -outdir .. ‘CFLAGS=$CFLAGS -Wno-overlength-strings -pedantic -Wno-long-long -Wno-declaration-after-statement -fwrapv’ -DMODEL=tutorial_matsim_start_spr_dmp_01 -DNUMST=1 -DNCSTATES=0 -DHAVESTDIO -DCLASSIC_INTERFACE=1 -DALLOCATIONFCN=0 -DTID01EQ=0 -DONESTEPFCN=0 -DTERMFCN=1 -DMULTI_INSTANCE_CODE=0 -DINTEGER_CODE=0 COPTIMFLAGS=-O0 -I.. -I..tutorial_matsim_start_spr_dmp_01_sfcn_rtw -IE:SOFTMATLABR2019bexterninclude -IE:SOFTMATLABR2019bsimulinkinclude -IE:SOFTMATLABR2019brtwcsrc tutorial_matsim_start_spr_dmp_01_sf.c rtGetInf.c rtGetNaN.c tutorial_matsim_start_spr_dmp_01_sf_data.c -LE:SOFTMATLABR2019bexternlibwin64mingw64 -lut -lfixedpoint ### Created mex file: ..tutorial_matsim_start_spr_dmp_01_sf.mexw64 ### Simulink cache artifacts for ‘tutorial_matsim_start_spr_dmp_01’ were created in ‘E:FILEtutorial_matsim_Isimulink_modeltutorial_matsim_start_spr_dmp_01.slxc’. 错误使用 getTMF Unable to locate template makefile: matsim_lcc64.tmf 出错 rtwprivate (line 16) [varargout{1:nargout}] = feval(function_name, varargin{1:end}); 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.getMexCompilerForModel 出错 coder.internal.ModelCompInfo/createModelCompInfoPrivate 出错 coder.internal.ModelCompInfo.createModelCompInfo 出错 slbuild_private 出错 sl (line 15) [varargout{1:nargout}]=feval(varargin{:}); 出错 slbuild (line 98) sl(‘slbuild_private’, mdl, target, varargin{2:end}); 出错 rtwbuild (line 235) slbuild(sys, ‘StandaloneCoderTarget’, … 出错 rtwbuildmatsim (line 70) rtwbuild(p.Results.model); – Show complete stack trace Displaying stack trace: Error using getTMF • In getTMF • In rtwprivate (line 16) • In coder.internal.getMexCompilerForModel • In coder.internal.getMexCompilerForModel • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfoPrivate • In coder.internal.ModelCompInfo>ModelCompInfo.createModelCompInfo • In slbuild_private • In sl (line 15) • In slbuild (line 98) • In rtwbuild (line 235) • In rtwbuildmatsim (line 70) error, mex compiler, simulink, toolbox MATLAB Answers — New Questions

​

I started using the Dependency Analyzer tool (in 2023b) to find out which Mathworks toolboxes are being invoked in my scripts and apps. I’m a bit confused on the output. So one of my scripts calls the ‘contains’ function. DA tool indicates the Mapping Toolbox is in use because it has a ‘contains’ function. However ‘which contains’ shows this is also in C:Program FilesMATLABR2023btoolboxmatlabstrfuncontains – and this is the right one.
So why is DA saying I’m using the Mapping Toolbox? Doesn’t it follow the Matlab path rules to find the right one (that takes priority)? Such output can be quite confusing and time-consuming. Or am I doing something wrong? Thanks for the guidance.
PVI started using the Dependency Analyzer tool (in 2023b) to find out which Mathworks toolboxes are being invoked in my scripts and apps. I’m a bit confused on the output. So one of my scripts calls the ‘contains’ function. DA tool indicates the Mapping Toolbox is in use because it has a ‘contains’ function. However ‘which contains’ shows this is also in C:Program FilesMATLABR2023btoolboxmatlabstrfuncontains – and this is the right one.
So why is DA saying I’m using the Mapping Toolbox? Doesn’t it follow the Matlab path rules to find the right one (that takes priority)? Such output can be quite confusing and time-consuming. Or am I doing something wrong? Thanks for the guidance.
PV I started using the Dependency Analyzer tool (in 2023b) to find out which Mathworks toolboxes are being invoked in my scripts and apps. I’m a bit confused on the output. So one of my scripts calls the ‘contains’ function. DA tool indicates the Mapping Toolbox is in use because it has a ‘contains’ function. However ‘which contains’ shows this is also in C:Program FilesMATLABR2023btoolboxmatlabstrfuncontains – and this is the right one.
So why is DA saying I’m using the Mapping Toolbox? Doesn’t it follow the Matlab path rules to find the right one (that takes priority)? Such output can be quite confusing and time-consuming. Or am I doing something wrong? Thanks for the guidance.
PV dependency analyzer, path MATLAB Answers — New Questions

​

%% R-RRR
clear all; clc; close all
% Input data
AB=0.325; %(m)
BC=0.938; %(m)
CD=0.675; %(m)
CE=0.6; %(m)
xD=0.8; %(m)
yD=-0.432; %(m)
phi =pi; %(rad)
xA = 0; yA = 0;
rA = [xA yA 0];
rD = [xD yD 0];
xB = AB*cos(phi); yB = AB*sin(phi); rB = [xB yB 0];
% Position of joint C
%
eqnC1 = ‘(xCsol – xB)^2 + (yCsol – yB)^2 = BC^2 ‘;
% Distance formula: CD=constant
eqnC2 = ‘(xCsol – xD)^2 + (yCsol – yD)^2 = CD^2 ‘;
% Simultaneously solve above equations
solC = solve(eqnC1, eqnC2, ‘xCsol, yCsol’);
% Two solutions for xC – vector form
xCpositions = eval(solC.xCsol);
% Two solutions for yC – vector form
yCpositions = eval(solC.yCsol);
% Separate the solutions in scalar form
% first component of the vector xCpositions
xC1 = xCpositions(1);
% second component of the vector xCpositions
xC2 = xCpositions(2);

yC1 = yCpositions(1);
% second component of the vector yCpositions
yC2 = yCpositions(2);
% Select the correct position for C
% for the given input angle
if xC1 > xD
xC = xC1; yC=yC1;
else
xC = xC2; yC=yC2;
end
rC = [xC yC 0]; % Position vector of C
% Position of joint E
% Distance formula: CE=constant
eqnE1='(xEsol-xC)^2+(yEsol-yC)^2=CE^2′;
% Slope formula:
% E, C, and D are on the same straight line
eqnE2='(yD-yC)/(xD-xC)=(yEsol-yC)/(xEsol-xC)’;
solE = solve(eqnE1, eqnE2, ‘xEsol, yEsol’);
xEpositions = eval(solE.xEsol);
yEpositions = eval(solE.yEsol);
xE1 = xEpositions(1); xE2 = xEpositions(2);
yE1 = yEpositions(1); yE2 = yEpositions(2);
if xE1 < xC
xE = xE1; yE=yE1;
else
xE = xE2; yE=yE2;
end
rE = [xE yE 0]; % Position vector of E
% Angles of the links with the horizontal
phi2 = atan((yB-yC)/(xB-xC));
phi3 = atan((yD-yC)/(xD-xC));
fprintf(‘Results nn’)
fprintf(‘rA = [ %g, %g, %g ] (m)n’, rA)
fprintf(‘rD = [ %g, %g, %g ] (m)n’, rD)
fprintf(‘rB = [ %g, %g, %g ] (m)n’, rB)
fprintf(‘rC = [ %g, %g, %g ] (m)n’, rC)
fprintf(‘rE = [ %g, %g, %g ] (m)n’, rE)
fprintf(‘phi2 = %g (degrees) n’, phi2*180/pi)
fprintf(‘phi3 = %g (degrees) n’, phi3*180/pi)

% Graphic of the mechanism
plot([xA,xB],[yA,yB],’k-o’,’LineWidth’,1.5)
hold on % holds the current plot
plot([xB,xC],[yB,yC],’b-o’,’LineWidth’,1.5)
hold on
plot([xD,xE],[yD,yE],’r-o’,’LineWidth’,1.5)
% adds major grid lines to the current axes
grid on,…
xlabel(‘x (m)’), ylabel(‘y (m)’),…
title(‘positions for phi = 45 (deg)’),…
text(xA,yA,’leftarrow A = ground’,…
‘HorizontalAlignment’,’left’),…
text(xB,yB,’ B’),…
text(xC,yC,’leftarrow C = ground’,…
‘HorizontalAlignment’,’left’),…
text(xD,yD,’leftarrow D = ground’,…
‘HorizontalAlignment’,’left’),…
text(xE,yE,’ E’), axis([-2 3 -2 3])%% R-RRR
clear all; clc; close all
% Input data
AB=0.325; %(m)
BC=0.938; %(m)
CD=0.675; %(m)
CE=0.6; %(m)
xD=0.8; %(m)
yD=-0.432; %(m)
phi =pi; %(rad)
xA = 0; yA = 0;
rA = [xA yA 0];
rD = [xD yD 0];
xB = AB*cos(phi); yB = AB*sin(phi); rB = [xB yB 0];
% Position of joint C
%
eqnC1 = ‘(xCsol – xB)^2 + (yCsol – yB)^2 = BC^2 ‘;
% Distance formula: CD=constant
eqnC2 = ‘(xCsol – xD)^2 + (yCsol – yD)^2 = CD^2 ‘;
% Simultaneously solve above equations
solC = solve(eqnC1, eqnC2, ‘xCsol, yCsol’);
% Two solutions for xC – vector form
xCpositions = eval(solC.xCsol);
% Two solutions for yC – vector form
yCpositions = eval(solC.yCsol);
% Separate the solutions in scalar form
% first component of the vector xCpositions
xC1 = xCpositions(1);
% second component of the vector xCpositions
xC2 = xCpositions(2);

yC1 = yCpositions(1);
% second component of the vector yCpositions
yC2 = yCpositions(2);
% Select the correct position for C
% for the given input angle
if xC1 > xD
xC = xC1; yC=yC1;
else
xC = xC2; yC=yC2;
end
rC = [xC yC 0]; % Position vector of C
% Position of joint E
% Distance formula: CE=constant
eqnE1='(xEsol-xC)^2+(yEsol-yC)^2=CE^2′;
% Slope formula:
% E, C, and D are on the same straight line
eqnE2='(yD-yC)/(xD-xC)=(yEsol-yC)/(xEsol-xC)’;
solE = solve(eqnE1, eqnE2, ‘xEsol, yEsol’);
xEpositions = eval(solE.xEsol);
yEpositions = eval(solE.yEsol);
xE1 = xEpositions(1); xE2 = xEpositions(2);
yE1 = yEpositions(1); yE2 = yEpositions(2);
if xE1 < xC
xE = xE1; yE=yE1;
else
xE = xE2; yE=yE2;
end
rE = [xE yE 0]; % Position vector of E
% Angles of the links with the horizontal
phi2 = atan((yB-yC)/(xB-xC));
phi3 = atan((yD-yC)/(xD-xC));
fprintf(‘Results nn’)
fprintf(‘rA = [ %g, %g, %g ] (m)n’, rA)
fprintf(‘rD = [ %g, %g, %g ] (m)n’, rD)
fprintf(‘rB = [ %g, %g, %g ] (m)n’, rB)
fprintf(‘rC = [ %g, %g, %g ] (m)n’, rC)
fprintf(‘rE = [ %g, %g, %g ] (m)n’, rE)
fprintf(‘phi2 = %g (degrees) n’, phi2*180/pi)
fprintf(‘phi3 = %g (degrees) n’, phi3*180/pi)

% Graphic of the mechanism
plot([xA,xB],[yA,yB],’k-o’,’LineWidth’,1.5)
hold on % holds the current plot
plot([xB,xC],[yB,yC],’b-o’,’LineWidth’,1.5)
hold on
plot([xD,xE],[yD,yE],’r-o’,’LineWidth’,1.5)
% adds major grid lines to the current axes
grid on,…
xlabel(‘x (m)’), ylabel(‘y (m)’),…
title(‘positions for phi = 45 (deg)’),…
text(xA,yA,’leftarrow A = ground’,…
‘HorizontalAlignment’,’left’),…
text(xB,yB,’ B’),…
text(xC,yC,’leftarrow C = ground’,…
‘HorizontalAlignment’,’left’),…
text(xD,yD,’leftarrow D = ground’,…
‘HorizontalAlignment’,’left’),…
text(xE,yE,’ E’), axis([-2 3 -2 3]) %% R-RRR
clear all; clc; close all
% Input data
AB=0.325; %(m)
BC=0.938; %(m)
CD=0.675; %(m)
CE=0.6; %(m)
xD=0.8; %(m)
yD=-0.432; %(m)
phi =pi; %(rad)
xA = 0; yA = 0;
rA = [xA yA 0];
rD = [xD yD 0];
xB = AB*cos(phi); yB = AB*sin(phi); rB = [xB yB 0];
% Position of joint C
%
eqnC1 = ‘(xCsol – xB)^2 + (yCsol – yB)^2 = BC^2 ‘;
% Distance formula: CD=constant
eqnC2 = ‘(xCsol – xD)^2 + (yCsol – yD)^2 = CD^2 ‘;
% Simultaneously solve above equations
solC = solve(eqnC1, eqnC2, ‘xCsol, yCsol’);
% Two solutions for xC – vector form
xCpositions = eval(solC.xCsol);
% Two solutions for yC – vector form
yCpositions = eval(solC.yCsol);
% Separate the solutions in scalar form
% first component of the vector xCpositions
xC1 = xCpositions(1);
% second component of the vector xCpositions
xC2 = xCpositions(2);

yC1 = yCpositions(1);
% second component of the vector yCpositions
yC2 = yCpositions(2);
% Select the correct position for C
% for the given input angle
if xC1 > xD
xC = xC1; yC=yC1;
else
xC = xC2; yC=yC2;
end
rC = [xC yC 0]; % Position vector of C
% Position of joint E
% Distance formula: CE=constant
eqnE1='(xEsol-xC)^2+(yEsol-yC)^2=CE^2′;
% Slope formula:
% E, C, and D are on the same straight line
eqnE2='(yD-yC)/(xD-xC)=(yEsol-yC)/(xEsol-xC)’;
solE = solve(eqnE1, eqnE2, ‘xEsol, yEsol’);
xEpositions = eval(solE.xEsol);
yEpositions = eval(solE.yEsol);
xE1 = xEpositions(1); xE2 = xEpositions(2);
yE1 = yEpositions(1); yE2 = yEpositions(2);
if xE1 < xC
xE = xE1; yE=yE1;
else
xE = xE2; yE=yE2;
end
rE = [xE yE 0]; % Position vector of E
% Angles of the links with the horizontal
phi2 = atan((yB-yC)/(xB-xC));
phi3 = atan((yD-yC)/(xD-xC));
fprintf(‘Results nn’)
fprintf(‘rA = [ %g, %g, %g ] (m)n’, rA)
fprintf(‘rD = [ %g, %g, %g ] (m)n’, rD)
fprintf(‘rB = [ %g, %g, %g ] (m)n’, rB)
fprintf(‘rC = [ %g, %g, %g ] (m)n’, rC)
fprintf(‘rE = [ %g, %g, %g ] (m)n’, rE)
fprintf(‘phi2 = %g (degrees) n’, phi2*180/pi)
fprintf(‘phi3 = %g (degrees) n’, phi3*180/pi)

% Graphic of the mechanism
plot([xA,xB],[yA,yB],’k-o’,’LineWidth’,1.5)
hold on % holds the current plot
plot([xB,xC],[yB,yC],’b-o’,’LineWidth’,1.5)
hold on
plot([xD,xE],[yD,yE],’r-o’,’LineWidth’,1.5)
% adds major grid lines to the current axes
grid on,…
xlabel(‘x (m)’), ylabel(‘y (m)’),…
title(‘positions for phi = 45 (deg)’),…
text(xA,yA,’leftarrow A = ground’,…
‘HorizontalAlignment’,’left’),…
text(xB,yB,’ B’),…
text(xC,yC,’leftarrow C = ground’,…
‘HorizontalAlignment’,’left’),…
text(xD,yD,’leftarrow D = ground’,…
‘HorizontalAlignment’,’left’),…
text(xE,yE,’ E’), axis([-2 3 -2 3]) plot MATLAB Answers — New Questions

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Adaptive PID control using simulink’s own Agent. Since the first 20 is a buffer process for the system, the first 20s are not part of the transition process, but are necessary to exist. How to make the Agent block the first 20s of action, state, reward and other information, or how to make the first 20s does not affect the training effect. In fact, if the first 10s are learned by the intelligent body, then the training effect is very poor.Adaptive PID control using simulink’s own Agent. Since the first 20 is a buffer process for the system, the first 20s are not part of the transition process, but are necessary to exist. How to make the Agent block the first 20s of action, state, reward and other information, or how to make the first 20s does not affect the training effect. In fact, if the first 10s are learned by the intelligent body, then the training effect is very poor. Adaptive PID control using simulink’s own Agent. Since the first 20 is a buffer process for the system, the first 20s are not part of the transition process, but are necessary to exist. How to make the Agent block the first 20s of action, state, reward and other information, or how to make the first 20s does not affect the training effect. In fact, if the first 10s are learned by the intelligent body, then the training effect is very poor. reinforcement learning, simulink, agent MATLAB Answers — New Questions

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Hi there!
I am wondering if there is the matlab code for sinusoidal representation networks or SIRENs, which are suitable for solving PDEs in the frame of PINNs. The activation function of an SIREN in sin function, this activation layer has not been built in Matlab.

Thanks for any help.Hi there!
I am wondering if there is the matlab code for sinusoidal representation networks or SIRENs, which are suitable for solving PDEs in the frame of PINNs. The activation function of an SIREN in sin function, this activation layer has not been built in Matlab.

Thanks for any help. Hi there!
I am wondering if there is the matlab code for sinusoidal representation networks or SIRENs, which are suitable for solving PDEs in the frame of PINNs. The activation function of an SIREN in sin function, this activation layer has not been built in Matlab.

Thanks for any help. deep learning, pinns, siren MATLAB Answers — New Questions

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