I am loading one Excel spreadsheet with 11 tabs. The 11 tabs are named fl1, fl2,… fl11.
The spreadsheet is currently loaded into a structure named flight_data. I don’t like the way it is organized, so I want to create a 11 new structures: somename1, somename2,….somename11.
I think the code will show how I’m trying to structure my data. The goal is to have 11 strutures that look like this:
%my loop that doesn’t work

for i = 1:11
fpro(i).loc7.x = flight_data.fpro{i}(:,1)
end

%my structure setup
fpro(i).name = ‘Flight Profile {i}’;

fpro(i).loc7.x = flight_data.fl{i}(:,1)
fpro(i).loc9.x = flight_data.fl{i}(:,4)
fpro(i).loc10.x = flight_data.fl{i}(:,7)

fpro(i).loc7.y = flight_data.fl{i}(:,2)
fpro(i).loc9.y = flight_data.fl{i}(:,5)
fpro(i).loc10.y = flight_data.fl{i}(:,8)

fpro(i).loc7.z = flight_data.fl{i}(:,3)
fpro(i).loc9.z = flight_data.fl{i}(:,6)
fpro(i).loc10.z = flight_data.fl{i}(:,9)I am loading one Excel spreadsheet with 11 tabs. The 11 tabs are named fl1, fl2,… fl11.
The spreadsheet is currently loaded into a structure named flight_data. I don’t like the way it is organized, so I want to create a 11 new structures: somename1, somename2,….somename11.
I think the code will show how I’m trying to structure my data. The goal is to have 11 strutures that look like this:
%my loop that doesn’t work

for i = 1:11
fpro(i).loc7.x = flight_data.fpro{i}(:,1)
end

%my structure setup
fpro(i).name = ‘Flight Profile {i}’;

fpro(i).loc7.x = flight_data.fl{i}(:,1)
fpro(i).loc9.x = flight_data.fl{i}(:,4)
fpro(i).loc10.x = flight_data.fl{i}(:,7)

fpro(i).loc7.y = flight_data.fl{i}(:,2)
fpro(i).loc9.y = flight_data.fl{i}(:,5)
fpro(i).loc10.y = flight_data.fl{i}(:,8)

fpro(i).loc7.z = flight_data.fl{i}(:,3)
fpro(i).loc9.z = flight_data.fl{i}(:,6)
fpro(i).loc10.z = flight_data.fl{i}(:,9) I am loading one Excel spreadsheet with 11 tabs. The 11 tabs are named fl1, fl2,… fl11.
The spreadsheet is currently loaded into a structure named flight_data. I don’t like the way it is organized, so I want to create a 11 new structures: somename1, somename2,….somename11.
I think the code will show how I’m trying to structure my data. The goal is to have 11 strutures that look like this:
%my loop that doesn’t work

for i = 1:11
fpro(i).loc7.x = flight_data.fpro{i}(:,1)
end

%my structure setup
fpro(i).name = ‘Flight Profile {i}’;

fpro(i).loc7.x = flight_data.fl{i}(:,1)
fpro(i).loc9.x = flight_data.fl{i}(:,4)
fpro(i).loc10.x = flight_data.fl{i}(:,7)

fpro(i).loc7.y = flight_data.fl{i}(:,2)
fpro(i).loc9.y = flight_data.fl{i}(:,5)
fpro(i).loc10.y = flight_data.fl{i}(:,8)

fpro(i).loc7.z = flight_data.fl{i}(:,3)
fpro(i).loc9.z = flight_data.fl{i}(:,6)
fpro(i).loc10.z = flight_data.fl{i}(:,9) for, structures, sytax MATLAB Answers — New Questions

​

When I run MATLAB R2021b on my Linux machine, it occasionally crashes.  The following error message appears in the terminal or at the top of the resulting crash stack trace:

Inconsistency detected by ld.so: ../elf/dl-tls.c: 597: _dl_allocate_tls_init: Assertion `listp != NULL’ failed!
This crash primarily happens when I attempt to use Simulink for the first time after launching MATLAB.When I run MATLAB R2021b on my Linux machine, it occasionally crashes.  The following error message appears in the terminal or at the top of the resulting crash stack trace:

Inconsistency detected by ld.so: ../elf/dl-tls.c: 597: _dl_allocate_tls_init: Assertion `listp != NULL’ failed!
This crash primarily happens when I attempt to use Simulink for the first time after launching MATLAB. When I run MATLAB R2021b on my Linux machine, it occasionally crashes.  The following error message appears in the terminal or at the top of the resulting crash stack trace:

Inconsistency detected by ld.so: ../elf/dl-tls.c: 597: _dl_allocate_tls_init: Assertion `listp != NULL’ failed!
This crash primarily happens when I attempt to use Simulink for the first time after launching MATLAB. crash, libc, linux, glibc MATLAB Answers — New Questions

​

Has anyone modeled a dc motor and resolver in multibody or other? Looking for an example rather brute force attempting including learning curve.Has anyone modeled a dc motor and resolver in multibody or other? Looking for an example rather brute force attempting including learning curve. Has anyone modeled a dc motor and resolver in multibody or other? Looking for an example rather brute force attempting including learning curve. resolver MATLAB Answers — New Questions

​

Hi,
I programmatically need to change signal names in simulink.
I use a code similar to:

lineH = find_system(gcs, ‘FindAll’, ‘on’, ‘type’, ‘line’);
set(lineH, ‘Name’, ‘NewName’);

So far so good, but when the changed signal is fed into a bus and should then be selected with a bus selector block, the selector block does not find the "NewName".

I would need to manually open the bus selector block and select the "NewName". Problem is, that there are hundrets of signals to be changed and even much more bus selectors, where the change needs then to be done manually.

Interresting is, that if a signal name change in Simulink is done manually, the bus selectors are somehow updated and the "NewName" is detected automatically without the need of selecting the signal in the respective bus selectors.

Has anyone a solution for this problem?
It would be nice, if there was a built in matlab/simulink function that can automatically update all bus selectors after a programmatically performed signal name change?

Thanks for you help.
ThomasHi,
I programmatically need to change signal names in simulink.
I use a code similar to:

lineH = find_system(gcs, ‘FindAll’, ‘on’, ‘type’, ‘line’);
set(lineH, ‘Name’, ‘NewName’);

So far so good, but when the changed signal is fed into a bus and should then be selected with a bus selector block, the selector block does not find the "NewName".

I would need to manually open the bus selector block and select the "NewName". Problem is, that there are hundrets of signals to be changed and even much more bus selectors, where the change needs then to be done manually.

Interresting is, that if a signal name change in Simulink is done manually, the bus selectors are somehow updated and the "NewName" is detected automatically without the need of selecting the signal in the respective bus selectors.

Has anyone a solution for this problem?
It would be nice, if there was a built in matlab/simulink function that can automatically update all bus selectors after a programmatically performed signal name change?

Thanks for you help.
Thomas Hi,
I programmatically need to change signal names in simulink.
I use a code similar to:

lineH = find_system(gcs, ‘FindAll’, ‘on’, ‘type’, ‘line’);
set(lineH, ‘Name’, ‘NewName’);

So far so good, but when the changed signal is fed into a bus and should then be selected with a bus selector block, the selector block does not find the "NewName".

I would need to manually open the bus selector block and select the "NewName". Problem is, that there are hundrets of signals to be changed and even much more bus selectors, where the change needs then to be done manually.

Interresting is, that if a signal name change in Simulink is done manually, the bus selectors are somehow updated and the "NewName" is detected automatically without the need of selecting the signal in the respective bus selectors.

Has anyone a solution for this problem?
It would be nice, if there was a built in matlab/simulink function that can automatically update all bus selectors after a programmatically performed signal name change?

Thanks for you help.
Thomas busselector, bus selector, programmatically, signal name change programmatically, signal name change, programmatically change simulink signal name, signal name change with m script MATLAB Answers — New Questions

​

clear
m0=1;
lamda=532*10^(-9);%lamda=[417,457,488,532,632.8]*10^(-9); %光束波长
z=50;%z=eps+[0:5:50]; %传播距离
R=0.03;%接受孔径的半径
A0=10;%光束功率常数
det=0.01:0.01:0.15; %横向相干长度
L=[1,5,10,20,30];%光总数指数
e=1*10^(-5);%e=[0.01,0.1,1,10,100]*10^(-5);%动能耗散率
X=1*10^(-8);% 温度耗5散
eta=0.001;% 内尺度因子
abc=3;%各项异性子
gama=-3;%温度盐度贡献比
NUM=10;
m=m0-NUM:1:m0+NUM;
k=2*pi/lamda;

for iiii=1:length(L)
C0=0;
for ll=1:L(iiii)
C0=C0+factorial(L(iiii))/factorial(ll)/factorial(L(iiii)-ll)*(-1)^(ll-1)/ll;
end
for iii=1:length(det)
for ii=1:length(m)
qtemp=0;
funt1=pi^2/(k*z)*(factorial(m0)*A0)^2/C0;
rouc2=8.705*10^(-8)*k^2*(e*eta)^(-1/3)*abc^(-2)*X*z*(1-2.605*gama^(-1)+7.007*gama^(-2));
for lll=1:L(iiii)
funt2=factorial(L(iiii))/(factorial(lll)*factorial(L(iiii)-lll))*(-1)^(lll-1)/lll;
fun=@(r) r.*funt1.*funt2.*(besselj(m0./2,k./4./z.*r.^2)).^2.*exp(-r.^2*(1./(lll.*det(iii).^2)+2.*rouc2))…
.*besseli(m(ii)-m0,(1./(lll.*det(iii).^2)+2.*rouc2).*r.^2);
qtemp=qtemp+integral(fun,0,R);
end
q(ii)=qtemp;
end
P(iiii,iii)=q(NUM+1)/sum(q);
end
end
figure
plot(det,P(1,:),’rs-‘);hold on
plot(det,P(2,:),’b+-‘);hold on
plot(det,P(3,:),’c*-‘);hold on
plot(det,P(4,:),’md-‘);hold on
plot(det,P(5,:),’g^-‘);
legend(‘L=1′,’L=5′,’L=10′,’L=20′,’L=30’)
%legend(‘λ=417nm’,’λ=457nm’,’λ=488nm’,’λ=532nm’,’λ=632.8nm’)
%legend(‘e=10^{-5}’,’e=3*10^{-5}’,’e=5*10^{-5}’,’e=7*10^{-5}’,’e=9*10^{-5}’)
xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
axis([0.01,0.15,0.35,0.85]);hold on
demo1 = 0.35:0.1:0.85;
demo2 = [0.01,0.03,0.06,0.09,0.12,0.15];%demo2 = 0.01:0.02:0.1;
set(gca,’yTick’,demo1)
set(gca,’xTick’,demo2)
%xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
%axis([0.01,0.1,0.35,0.85]);hold on
%demo1 = 0.35:0.1:0.85;
%demo2 = 0.01:0.02:0.1;
%set(gca,’yTick’,demo1)
%set(gca,’xTick’,demo2)
% [X0,Y0] = meshgrid(lamda,det);
% figure,surf(X0,Y0,P)
% %figure,bar3(P)
% xlabel(‘lamda’);ylabel(‘det’);zlabel(‘P_{m_{0}}’);hold on

>> MHBew_beamindex_hengxiangxiangganchagndu
BLAS: trying environment BLAS_VERSION…
BLAS: loading C:MATLAB7binwin32atlas_Athlon.dll
BLAS: unloading libraries
错误使用 *
BLAS 加载错误:
C:MATLAB7binwin32atlas_Athlon.dll: 找不到指定的模块。

出错 integralCalc>iterateScalarValued (第 330 行)
x = NODES*halfh + midpt; % NNODES x nsubs

出错 integralCalc>vadapt (第 148 行)
[q,errbnd] = iterateScalarValued(u,tinterval,pathlen, …

出错 integralCalc (第 77 行)
[q,errbnd] = vadapt(vfunAB,interval, …

出错 integral (第 87 行)
Q = integralCalc(fun,a,b,opstruct);

出错 MHBew_beamindex_hengxiangxiangganchagndu (第 36 行)
qtemp=qtemp+integral(fun,0,R);clear
m0=1;
lamda=532*10^(-9);%lamda=[417,457,488,532,632.8]*10^(-9); %光束波长
z=50;%z=eps+[0:5:50]; %传播距离
R=0.03;%接受孔径的半径
A0=10;%光束功率常数
det=0.01:0.01:0.15; %横向相干长度
L=[1,5,10,20,30];%光总数指数
e=1*10^(-5);%e=[0.01,0.1,1,10,100]*10^(-5);%动能耗散率
X=1*10^(-8);% 温度耗5散
eta=0.001;% 内尺度因子
abc=3;%各项异性子
gama=-3;%温度盐度贡献比
NUM=10;
m=m0-NUM:1:m0+NUM;
k=2*pi/lamda;

for iiii=1:length(L)
C0=0;
for ll=1:L(iiii)
C0=C0+factorial(L(iiii))/factorial(ll)/factorial(L(iiii)-ll)*(-1)^(ll-1)/ll;
end
for iii=1:length(det)
for ii=1:length(m)
qtemp=0;
funt1=pi^2/(k*z)*(factorial(m0)*A0)^2/C0;
rouc2=8.705*10^(-8)*k^2*(e*eta)^(-1/3)*abc^(-2)*X*z*(1-2.605*gama^(-1)+7.007*gama^(-2));
for lll=1:L(iiii)
funt2=factorial(L(iiii))/(factorial(lll)*factorial(L(iiii)-lll))*(-1)^(lll-1)/lll;
fun=@(r) r.*funt1.*funt2.*(besselj(m0./2,k./4./z.*r.^2)).^2.*exp(-r.^2*(1./(lll.*det(iii).^2)+2.*rouc2))…
.*besseli(m(ii)-m0,(1./(lll.*det(iii).^2)+2.*rouc2).*r.^2);
qtemp=qtemp+integral(fun,0,R);
end
q(ii)=qtemp;
end
P(iiii,iii)=q(NUM+1)/sum(q);
end
end
figure
plot(det,P(1,:),’rs-‘);hold on
plot(det,P(2,:),’b+-‘);hold on
plot(det,P(3,:),’c*-‘);hold on
plot(det,P(4,:),’md-‘);hold on
plot(det,P(5,:),’g^-‘);
legend(‘L=1′,’L=5′,’L=10′,’L=20′,’L=30’)
%legend(‘λ=417nm’,’λ=457nm’,’λ=488nm’,’λ=532nm’,’λ=632.8nm’)
%legend(‘e=10^{-5}’,’e=3*10^{-5}’,’e=5*10^{-5}’,’e=7*10^{-5}’,’e=9*10^{-5}’)
xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
axis([0.01,0.15,0.35,0.85]);hold on
demo1 = 0.35:0.1:0.85;
demo2 = [0.01,0.03,0.06,0.09,0.12,0.15];%demo2 = 0.01:0.02:0.1;
set(gca,’yTick’,demo1)
set(gca,’xTick’,demo2)
%xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
%axis([0.01,0.1,0.35,0.85]);hold on
%demo1 = 0.35:0.1:0.85;
%demo2 = 0.01:0.02:0.1;
%set(gca,’yTick’,demo1)
%set(gca,’xTick’,demo2)
% [X0,Y0] = meshgrid(lamda,det);
% figure,surf(X0,Y0,P)
% %figure,bar3(P)
% xlabel(‘lamda’);ylabel(‘det’);zlabel(‘P_{m_{0}}’);hold on

>> MHBew_beamindex_hengxiangxiangganchagndu
BLAS: trying environment BLAS_VERSION…
BLAS: loading C:MATLAB7binwin32atlas_Athlon.dll
BLAS: unloading libraries
错误使用 *
BLAS 加载错误:
C:MATLAB7binwin32atlas_Athlon.dll: 找不到指定的模块。

出错 integralCalc>iterateScalarValued (第 330 行)
x = NODES*halfh + midpt; % NNODES x nsubs

出错 integralCalc>vadapt (第 148 行)
[q,errbnd] = iterateScalarValued(u,tinterval,pathlen, …

出错 integralCalc (第 77 行)
[q,errbnd] = vadapt(vfunAB,interval, …

出错 integral (第 87 行)
Q = integralCalc(fun,a,b,opstruct);

出错 MHBew_beamindex_hengxiangxiangganchagndu (第 36 行)
qtemp=qtemp+integral(fun,0,R); clear
m0=1;
lamda=532*10^(-9);%lamda=[417,457,488,532,632.8]*10^(-9); %光束波长
z=50;%z=eps+[0:5:50]; %传播距离
R=0.03;%接受孔径的半径
A0=10;%光束功率常数
det=0.01:0.01:0.15; %横向相干长度
L=[1,5,10,20,30];%光总数指数
e=1*10^(-5);%e=[0.01,0.1,1,10,100]*10^(-5);%动能耗散率
X=1*10^(-8);% 温度耗5散
eta=0.001;% 内尺度因子
abc=3;%各项异性子
gama=-3;%温度盐度贡献比
NUM=10;
m=m0-NUM:1:m0+NUM;
k=2*pi/lamda;

for iiii=1:length(L)
C0=0;
for ll=1:L(iiii)
C0=C0+factorial(L(iiii))/factorial(ll)/factorial(L(iiii)-ll)*(-1)^(ll-1)/ll;
end
for iii=1:length(det)
for ii=1:length(m)
qtemp=0;
funt1=pi^2/(k*z)*(factorial(m0)*A0)^2/C0;
rouc2=8.705*10^(-8)*k^2*(e*eta)^(-1/3)*abc^(-2)*X*z*(1-2.605*gama^(-1)+7.007*gama^(-2));
for lll=1:L(iiii)
funt2=factorial(L(iiii))/(factorial(lll)*factorial(L(iiii)-lll))*(-1)^(lll-1)/lll;
fun=@(r) r.*funt1.*funt2.*(besselj(m0./2,k./4./z.*r.^2)).^2.*exp(-r.^2*(1./(lll.*det(iii).^2)+2.*rouc2))…
.*besseli(m(ii)-m0,(1./(lll.*det(iii).^2)+2.*rouc2).*r.^2);
qtemp=qtemp+integral(fun,0,R);
end
q(ii)=qtemp;
end
P(iiii,iii)=q(NUM+1)/sum(q);
end
end
figure
plot(det,P(1,:),’rs-‘);hold on
plot(det,P(2,:),’b+-‘);hold on
plot(det,P(3,:),’c*-‘);hold on
plot(det,P(4,:),’md-‘);hold on
plot(det,P(5,:),’g^-‘);
legend(‘L=1′,’L=5′,’L=10′,’L=20′,’L=30’)
%legend(‘λ=417nm’,’λ=457nm’,’λ=488nm’,’λ=532nm’,’λ=632.8nm’)
%legend(‘e=10^{-5}’,’e=3*10^{-5}’,’e=5*10^{-5}’,’e=7*10^{-5}’,’e=9*10^{-5}’)
xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
axis([0.01,0.15,0.35,0.85]);hold on
demo1 = 0.35:0.1:0.85;
demo2 = [0.01,0.03,0.06,0.09,0.12,0.15];%demo2 = 0.01:0.02:0.1;
set(gca,’yTick’,demo1)
set(gca,’xTick’,demo2)
%xlabel(‘delta/m’);ylabel(‘P_{l_{0}}’);
%axis([0.01,0.1,0.35,0.85]);hold on
%demo1 = 0.35:0.1:0.85;
%demo2 = 0.01:0.02:0.1;
%set(gca,’yTick’,demo1)
%set(gca,’xTick’,demo2)
% [X0,Y0] = meshgrid(lamda,det);
% figure,surf(X0,Y0,P)
% %figure,bar3(P)
% xlabel(‘lamda’);ylabel(‘det’);zlabel(‘P_{m_{0}}’);hold on

>> MHBew_beamindex_hengxiangxiangganchagndu
BLAS: trying environment BLAS_VERSION…
BLAS: loading C:MATLAB7binwin32atlas_Athlon.dll
BLAS: unloading libraries
错误使用 *
BLAS 加载错误:
C:MATLAB7binwin32atlas_Athlon.dll: 找不到指定的模块。

出错 integralCalc>iterateScalarValued (第 330 行)
x = NODES*halfh + midpt; % NNODES x nsubs

出错 integralCalc>vadapt (第 148 行)
[q,errbnd] = iterateScalarValued(u,tinterval,pathlen, …

出错 integralCalc (第 77 行)
[q,errbnd] = vadapt(vfunAB,interval, …

出错 integral (第 87 行)
Q = integralCalc(fun,a,b,opstruct);

出错 MHBew_beamindex_hengxiangxiangganchagndu (第 36 行)
qtemp=qtemp+integral(fun,0,R); integral MATLAB Answers — New Questions

​

Greetings everyone, below is the code which generates the diverging portion of a supersonic nozzle using the Method Of Characteristics. How can I plot the Mach Number contours within the same plot along with a colorbar? Thank you!
%% Initialize datapoint matrices
clear
G=1.4;
Me = 2;
n = 55;
display = 1;
Km = zeros(n,n); % K- vlaues (Constant along right running characteristic lines)
Kp = zeros(n,n); % K+ vlaues (Constant along left running characteristic lines)
Theta = zeros(n,n); % Flow angles relative to the horizontal
Mu = zeros(n,n); % Mach angles
M = zeros(n,n); % Mach Numbers
x = zeros(n,n); % x-coordinates
y = zeros(n,n); % y-coordinates
%% Generate the contraction region using a 3rd order polynomial. Do not run this
%{
R = 287;
T0 = 300;
% Define the mach number in contraction region
uu = 25.0; %velocity in contraction region
a = sqrt(G*R*T0 – 0.5*(G-1)*uu^2); % local speed of sound
Mconv = uu/a; % Mach number
% Calculate the area ratio of contraction region
[~,~,~,~,area] = flowisentropic(G,Mconv); % area ratio
% Inlet convergent section geometry
y0 =1;
H_in = area * y0;
L_e = 1.5; %(1.0/3.0)*xwall(end);
%
[xconv,yconv] = Convergent_3rd(G,y0,H_in,L_e,n);
%}
%% Generate the convergent portion of a nozzle
% The inlet height/area and exit height/area(divergent) are same
% Therefore we have same A/A* = 1.6875
% Corresponding to Mach = 0.3722
%% Find NuMax (maximum expansion angle)
[~, NuMax, ~] = PMF(G,Me,0,0);
ThetaMax = NuMax/2;
%% Define some flow parameters of originating characteristic lines
dT = ThetaMax/n;
ThetaArc(:,1) = (0:dT:ThetaMax);
NuArc = ThetaArc;
KmArc = ThetaArc + NuArc;
[~, ~, MuArc(:,1)] = PMF(G,0,NuArc(:,1),0);
%% Coordinates of wall along curve from throat
y0 = 1; % Define throat half-height
ThroatCurveRadius = 1.5*y0; % Radius of curvature just downstream of the throat
% for larger factors, ywall deviates from A/A* preferred value is 1.1
%L_e = 1.1 * y0 * sind(ThetaMax);
[xarc, yarc] = Arc(ThroatCurveRadius,ThetaArc); % Finds x- and y-coordinates for given theta-values
yarc(:,1) = yarc(:,1) + y0; % Defines offset due to arc being above horizontal
%% Fill in missing datapoint info along first C+ line
% First centerline datapoint done manually
Km(:,1) = KmArc(2:length(KmArc),1);
Theta(:,1) = ThetaArc(2:length(KmArc),1);
Nu(:,1) = Theta(:,1);
Kp(:,1) = Theta(:,1)-Nu(:,1);
M(1,1) = 1.0;
Nu(1,1) = 0;
Mu(1,1) = 90;
y(1,1) = 0;
x(1,1) = xarc(2,1) + (y(1,1) – yarc(2,1))/tand((ThetaArc(2,1) – MuArc(2,1) – MuArc(2,1))/2);
% Finds the information at interior nodes along first C+ line
for i=2:n
[M(i,1), Nu(i,1), Mu(i,1)] = PMF(G,0,Nu(i,1),0);
s1 = tand((ThetaArc(i+1,1) – MuArc(i+1,1) + Theta(i,1) – Mu(i,1))/2);
s2 = tand((Theta(i-1,1) + Mu(i-1,1) + Theta(i,1) + Mu(i,1))/2);
x(i,1) = ((y(i-1,1)-x(i-1,1)*s2)-(yarc(i+1,1)-xarc(i+1,1)*s1))/(s1-s2);
y(i,1) = y(i-1,1) + (x(i,1)-x(i-1,1))*s2;

end
%% Find flow properties at remaining interior nodes
for j=2:n;
for i=1:n+1-j;

Km(i,j) = Km(i+1,j-1);

if i==1;

Theta(i,j) = 0;
Kp(i,j) = -Km(i,j);
Nu(i,j) = Km(i,j);
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
x(i,j) = x(i+1,j-1) – y(i+1,j-1)/s1;
y(i,j) = 0;

else

Kp(i,j) = Kp(i-1,j);
Theta(i,j) = (Km(i,j)+Kp(i,j))/2;
Nu(i,j) = (Km(i,j)-Kp(i,j))/2;
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
s2 = tand((Theta(i-1,j)+Mu(i-1,j)+Theta(i,j)+Mu(i,j))/2);
x(i,j) = ((y(i-1,j)-x(i-1,j)*s2)-(y(i+1,j-1)-x(i+1,j-1)*s1))/(s1-s2);
y(i,j) = y(i-1,j) + (x(i,j)-x(i-1,j))*s2;

end

end
end
%% Find wall node information
xwall = zeros(2*n,1);
ywall = xwall;
ThetaWall = ywall;
xwall(1:n,1) = xarc(2:length(xarc),1);
ywall(1:n,1) = yarc(2:length(xarc),1);
ThetaWall(1:n,1) = ThetaArc(2:length(xarc),1);
for i=1:n-1
ThetaWall(n+i,1) = ThetaWall(n-i,1);
end
for i=1:n

s1 = tand((ThetaWall(n+i-1,1) + ThetaWall(n+i,1))/2);
s2 = tand(Theta(n+1-i,i)+Mu(n+1-i,i));
xwall(n+i,1) = ((y(n+1-i,i)-x(n+1-i,i)*s2)-(ywall(n+i-1,1)-xwall(n+i-1,1)*s1))/(s1-s2);
ywall(n+i,1) = ywall(n+i-1,1) + (xwall(n+i,1)-xwall(n+i-1,1))*s1;

end
%% Provide wall geometry to user
assignin(‘caller’,’xwall’,xwall)
assignin(‘caller’,’ywall’,ywall)
assignin(‘caller’,’Coords’,[xwall ywall])
%% Generate the convergent portion of nozzle % do not run this
H_in = ywall(end);
L_e = xwall(end)*(1.0/3.0);
[xconv,yconv] = Convergent_new_3rd(y0,H_in,L_e,n);
%%
% Draw contour and characteristic web
if display == 1
plot(xwall,ywall,’-‘)
axis equal
axis([0 ceil(xwall(length(xwall),1)) 0 ceil(ywall(length(ywall),1))])
hold on
plot(xarc,yarc,’k-‘)

for i=1:n-1
plot(x(1:n+1-i,i),y(1:n+1-i,i))
end
for i=1:n
plot([xarc(i,1) x(i,1)],[yarc(i,1) y(i,1)])
plot([x(n+1-i,i) xwall(i+n,1)],[y(n+1-i,i) ywall(i+n,1)])
end
for c=1:n
for r=2:n+1-c
plot([x(c,r) x(c+1,r-1)],[y(c,r) y(c+1,r-1)])
end
end
xlabel(‘Length [x/y0]’)
ylabel(‘Height [y/y0]’)

endGreetings everyone, below is the code which generates the diverging portion of a supersonic nozzle using the Method Of Characteristics. How can I plot the Mach Number contours within the same plot along with a colorbar? Thank you!
%% Initialize datapoint matrices
clear
G=1.4;
Me = 2;
n = 55;
display = 1;
Km = zeros(n,n); % K- vlaues (Constant along right running characteristic lines)
Kp = zeros(n,n); % K+ vlaues (Constant along left running characteristic lines)
Theta = zeros(n,n); % Flow angles relative to the horizontal
Mu = zeros(n,n); % Mach angles
M = zeros(n,n); % Mach Numbers
x = zeros(n,n); % x-coordinates
y = zeros(n,n); % y-coordinates
%% Generate the contraction region using a 3rd order polynomial. Do not run this
%{
R = 287;
T0 = 300;
% Define the mach number in contraction region
uu = 25.0; %velocity in contraction region
a = sqrt(G*R*T0 – 0.5*(G-1)*uu^2); % local speed of sound
Mconv = uu/a; % Mach number
% Calculate the area ratio of contraction region
[~,~,~,~,area] = flowisentropic(G,Mconv); % area ratio
% Inlet convergent section geometry
y0 =1;
H_in = area * y0;
L_e = 1.5; %(1.0/3.0)*xwall(end);
%
[xconv,yconv] = Convergent_3rd(G,y0,H_in,L_e,n);
%}
%% Generate the convergent portion of a nozzle
% The inlet height/area and exit height/area(divergent) are same
% Therefore we have same A/A* = 1.6875
% Corresponding to Mach = 0.3722
%% Find NuMax (maximum expansion angle)
[~, NuMax, ~] = PMF(G,Me,0,0);
ThetaMax = NuMax/2;
%% Define some flow parameters of originating characteristic lines
dT = ThetaMax/n;
ThetaArc(:,1) = (0:dT:ThetaMax);
NuArc = ThetaArc;
KmArc = ThetaArc + NuArc;
[~, ~, MuArc(:,1)] = PMF(G,0,NuArc(:,1),0);
%% Coordinates of wall along curve from throat
y0 = 1; % Define throat half-height
ThroatCurveRadius = 1.5*y0; % Radius of curvature just downstream of the throat
% for larger factors, ywall deviates from A/A* preferred value is 1.1
%L_e = 1.1 * y0 * sind(ThetaMax);
[xarc, yarc] = Arc(ThroatCurveRadius,ThetaArc); % Finds x- and y-coordinates for given theta-values
yarc(:,1) = yarc(:,1) + y0; % Defines offset due to arc being above horizontal
%% Fill in missing datapoint info along first C+ line
% First centerline datapoint done manually
Km(:,1) = KmArc(2:length(KmArc),1);
Theta(:,1) = ThetaArc(2:length(KmArc),1);
Nu(:,1) = Theta(:,1);
Kp(:,1) = Theta(:,1)-Nu(:,1);
M(1,1) = 1.0;
Nu(1,1) = 0;
Mu(1,1) = 90;
y(1,1) = 0;
x(1,1) = xarc(2,1) + (y(1,1) – yarc(2,1))/tand((ThetaArc(2,1) – MuArc(2,1) – MuArc(2,1))/2);
% Finds the information at interior nodes along first C+ line
for i=2:n
[M(i,1), Nu(i,1), Mu(i,1)] = PMF(G,0,Nu(i,1),0);
s1 = tand((ThetaArc(i+1,1) – MuArc(i+1,1) + Theta(i,1) – Mu(i,1))/2);
s2 = tand((Theta(i-1,1) + Mu(i-1,1) + Theta(i,1) + Mu(i,1))/2);
x(i,1) = ((y(i-1,1)-x(i-1,1)*s2)-(yarc(i+1,1)-xarc(i+1,1)*s1))/(s1-s2);
y(i,1) = y(i-1,1) + (x(i,1)-x(i-1,1))*s2;

end
%% Find flow properties at remaining interior nodes
for j=2:n;
for i=1:n+1-j;

Km(i,j) = Km(i+1,j-1);

if i==1;

Theta(i,j) = 0;
Kp(i,j) = -Km(i,j);
Nu(i,j) = Km(i,j);
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
x(i,j) = x(i+1,j-1) – y(i+1,j-1)/s1;
y(i,j) = 0;

else

Kp(i,j) = Kp(i-1,j);
Theta(i,j) = (Km(i,j)+Kp(i,j))/2;
Nu(i,j) = (Km(i,j)-Kp(i,j))/2;
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
s2 = tand((Theta(i-1,j)+Mu(i-1,j)+Theta(i,j)+Mu(i,j))/2);
x(i,j) = ((y(i-1,j)-x(i-1,j)*s2)-(y(i+1,j-1)-x(i+1,j-1)*s1))/(s1-s2);
y(i,j) = y(i-1,j) + (x(i,j)-x(i-1,j))*s2;

end

end
end
%% Find wall node information
xwall = zeros(2*n,1);
ywall = xwall;
ThetaWall = ywall;
xwall(1:n,1) = xarc(2:length(xarc),1);
ywall(1:n,1) = yarc(2:length(xarc),1);
ThetaWall(1:n,1) = ThetaArc(2:length(xarc),1);
for i=1:n-1
ThetaWall(n+i,1) = ThetaWall(n-i,1);
end
for i=1:n

s1 = tand((ThetaWall(n+i-1,1) + ThetaWall(n+i,1))/2);
s2 = tand(Theta(n+1-i,i)+Mu(n+1-i,i));
xwall(n+i,1) = ((y(n+1-i,i)-x(n+1-i,i)*s2)-(ywall(n+i-1,1)-xwall(n+i-1,1)*s1))/(s1-s2);
ywall(n+i,1) = ywall(n+i-1,1) + (xwall(n+i,1)-xwall(n+i-1,1))*s1;

end
%% Provide wall geometry to user
assignin(‘caller’,’xwall’,xwall)
assignin(‘caller’,’ywall’,ywall)
assignin(‘caller’,’Coords’,[xwall ywall])
%% Generate the convergent portion of nozzle % do not run this
H_in = ywall(end);
L_e = xwall(end)*(1.0/3.0);
[xconv,yconv] = Convergent_new_3rd(y0,H_in,L_e,n);
%%
% Draw contour and characteristic web
if display == 1
plot(xwall,ywall,’-‘)
axis equal
axis([0 ceil(xwall(length(xwall),1)) 0 ceil(ywall(length(ywall),1))])
hold on
plot(xarc,yarc,’k-‘)

for i=1:n-1
plot(x(1:n+1-i,i),y(1:n+1-i,i))
end
for i=1:n
plot([xarc(i,1) x(i,1)],[yarc(i,1) y(i,1)])
plot([x(n+1-i,i) xwall(i+n,1)],[y(n+1-i,i) ywall(i+n,1)])
end
for c=1:n
for r=2:n+1-c
plot([x(c,r) x(c+1,r-1)],[y(c,r) y(c+1,r-1)])
end
end
xlabel(‘Length [x/y0]’)
ylabel(‘Height [y/y0]’)

end Greetings everyone, below is the code which generates the diverging portion of a supersonic nozzle using the Method Of Characteristics. How can I plot the Mach Number contours within the same plot along with a colorbar? Thank you!
%% Initialize datapoint matrices
clear
G=1.4;
Me = 2;
n = 55;
display = 1;
Km = zeros(n,n); % K- vlaues (Constant along right running characteristic lines)
Kp = zeros(n,n); % K+ vlaues (Constant along left running characteristic lines)
Theta = zeros(n,n); % Flow angles relative to the horizontal
Mu = zeros(n,n); % Mach angles
M = zeros(n,n); % Mach Numbers
x = zeros(n,n); % x-coordinates
y = zeros(n,n); % y-coordinates
%% Generate the contraction region using a 3rd order polynomial. Do not run this
%{
R = 287;
T0 = 300;
% Define the mach number in contraction region
uu = 25.0; %velocity in contraction region
a = sqrt(G*R*T0 – 0.5*(G-1)*uu^2); % local speed of sound
Mconv = uu/a; % Mach number
% Calculate the area ratio of contraction region
[~,~,~,~,area] = flowisentropic(G,Mconv); % area ratio
% Inlet convergent section geometry
y0 =1;
H_in = area * y0;
L_e = 1.5; %(1.0/3.0)*xwall(end);
%
[xconv,yconv] = Convergent_3rd(G,y0,H_in,L_e,n);
%}
%% Generate the convergent portion of a nozzle
% The inlet height/area and exit height/area(divergent) are same
% Therefore we have same A/A* = 1.6875
% Corresponding to Mach = 0.3722
%% Find NuMax (maximum expansion angle)
[~, NuMax, ~] = PMF(G,Me,0,0);
ThetaMax = NuMax/2;
%% Define some flow parameters of originating characteristic lines
dT = ThetaMax/n;
ThetaArc(:,1) = (0:dT:ThetaMax);
NuArc = ThetaArc;
KmArc = ThetaArc + NuArc;
[~, ~, MuArc(:,1)] = PMF(G,0,NuArc(:,1),0);
%% Coordinates of wall along curve from throat
y0 = 1; % Define throat half-height
ThroatCurveRadius = 1.5*y0; % Radius of curvature just downstream of the throat
% for larger factors, ywall deviates from A/A* preferred value is 1.1
%L_e = 1.1 * y0 * sind(ThetaMax);
[xarc, yarc] = Arc(ThroatCurveRadius,ThetaArc); % Finds x- and y-coordinates for given theta-values
yarc(:,1) = yarc(:,1) + y0; % Defines offset due to arc being above horizontal
%% Fill in missing datapoint info along first C+ line
% First centerline datapoint done manually
Km(:,1) = KmArc(2:length(KmArc),1);
Theta(:,1) = ThetaArc(2:length(KmArc),1);
Nu(:,1) = Theta(:,1);
Kp(:,1) = Theta(:,1)-Nu(:,1);
M(1,1) = 1.0;
Nu(1,1) = 0;
Mu(1,1) = 90;
y(1,1) = 0;
x(1,1) = xarc(2,1) + (y(1,1) – yarc(2,1))/tand((ThetaArc(2,1) – MuArc(2,1) – MuArc(2,1))/2);
% Finds the information at interior nodes along first C+ line
for i=2:n
[M(i,1), Nu(i,1), Mu(i,1)] = PMF(G,0,Nu(i,1),0);
s1 = tand((ThetaArc(i+1,1) – MuArc(i+1,1) + Theta(i,1) – Mu(i,1))/2);
s2 = tand((Theta(i-1,1) + Mu(i-1,1) + Theta(i,1) + Mu(i,1))/2);
x(i,1) = ((y(i-1,1)-x(i-1,1)*s2)-(yarc(i+1,1)-xarc(i+1,1)*s1))/(s1-s2);
y(i,1) = y(i-1,1) + (x(i,1)-x(i-1,1))*s2;

end
%% Find flow properties at remaining interior nodes
for j=2:n;
for i=1:n+1-j;

Km(i,j) = Km(i+1,j-1);

if i==1;

Theta(i,j) = 0;
Kp(i,j) = -Km(i,j);
Nu(i,j) = Km(i,j);
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
x(i,j) = x(i+1,j-1) – y(i+1,j-1)/s1;
y(i,j) = 0;

else

Kp(i,j) = Kp(i-1,j);
Theta(i,j) = (Km(i,j)+Kp(i,j))/2;
Nu(i,j) = (Km(i,j)-Kp(i,j))/2;
[M(i,j), Nu(i,j), Mu(i,j)] = PMF(G,0,Nu(i,j),0);
s1 = tand((Theta(i+1,j-1)-Mu(i+1,j-1)+Theta(i,j)-Mu(i,j))/2);
s2 = tand((Theta(i-1,j)+Mu(i-1,j)+Theta(i,j)+Mu(i,j))/2);
x(i,j) = ((y(i-1,j)-x(i-1,j)*s2)-(y(i+1,j-1)-x(i+1,j-1)*s1))/(s1-s2);
y(i,j) = y(i-1,j) + (x(i,j)-x(i-1,j))*s2;

end

end
end
%% Find wall node information
xwall = zeros(2*n,1);
ywall = xwall;
ThetaWall = ywall;
xwall(1:n,1) = xarc(2:length(xarc),1);
ywall(1:n,1) = yarc(2:length(xarc),1);
ThetaWall(1:n,1) = ThetaArc(2:length(xarc),1);
for i=1:n-1
ThetaWall(n+i,1) = ThetaWall(n-i,1);
end
for i=1:n

s1 = tand((ThetaWall(n+i-1,1) + ThetaWall(n+i,1))/2);
s2 = tand(Theta(n+1-i,i)+Mu(n+1-i,i));
xwall(n+i,1) = ((y(n+1-i,i)-x(n+1-i,i)*s2)-(ywall(n+i-1,1)-xwall(n+i-1,1)*s1))/(s1-s2);
ywall(n+i,1) = ywall(n+i-1,1) + (xwall(n+i,1)-xwall(n+i-1,1))*s1;

end
%% Provide wall geometry to user
assignin(‘caller’,’xwall’,xwall)
assignin(‘caller’,’ywall’,ywall)
assignin(‘caller’,’Coords’,[xwall ywall])
%% Generate the convergent portion of nozzle % do not run this
H_in = ywall(end);
L_e = xwall(end)*(1.0/3.0);
[xconv,yconv] = Convergent_new_3rd(y0,H_in,L_e,n);
%%
% Draw contour and characteristic web
if display == 1
plot(xwall,ywall,’-‘)
axis equal
axis([0 ceil(xwall(length(xwall),1)) 0 ceil(ywall(length(ywall),1))])
hold on
plot(xarc,yarc,’k-‘)

for i=1:n-1
plot(x(1:n+1-i,i),y(1:n+1-i,i))
end
for i=1:n
plot([xarc(i,1) x(i,1)],[yarc(i,1) y(i,1)])
plot([x(n+1-i,i) xwall(i+n,1)],[y(n+1-i,i) ywall(i+n,1)])
end
for c=1:n
for r=2:n+1-c
plot([x(c,r) x(c+1,r-1)],[y(c,r) y(c+1,r-1)])
end
end
xlabel(‘Length [x/y0]’)
ylabel(‘Height [y/y0]’)

end #contour plot, nozzle, mach number MATLAB Answers — New Questions

​

Is there an AI for matlab scripts and simulink drawings? (I am not asking how to BUILD an AI system.I am asking for help with scripting and simulink via a Mathworks ai site)Is there an AI for matlab scripts and simulink drawings? (I am not asking how to BUILD an AI system.I am asking for help with scripting and simulink via a Mathworks ai site) Is there an AI for matlab scripts and simulink drawings? (I am not asking how to BUILD an AI system.I am asking for help with scripting and simulink via a Mathworks ai site) ai, scripting, simulink, help, make easy, website, free MATLAB Answers — New Questions

​

I am working on creating a model in Simulink that allows me to control a Turtlebot waffle pi so that it moves along a 6-point path. Along the path there will be obstacles in the form of red and green spheres. The objective is for the robot to reach all the points of the path avoiding the obstacles, if the sphere is red, avoid to the right and if it is green, avoid to the left.
I have already created the following Simulink model where the most important thing is in the control function since it describes the behavior of the robot, however the error that keeps appearing is the following: Error: Block ”Project_3/MATLAB Function” does not fully set the dimensions of output ‘next_index’. Which I do not find sense since the variable next_index is defined from the beginning. I attach the images of the model that I am creating.

function [area, x_obst, y_obst, target_x, target_y, obstacle, current_index, target_theta,last_point] = WaypointSelector(a, cent, waypoints, current_index)
%Extract obstacle’s area and position
[~,i] = max(a);
area = max(a);
if ~isempty(i)
obstacle = cent(i,:);
else
obstacle = [0,0];
end
% Cordanates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);
% Extract target waypoint
target_x = waypoints(current_index, 1);
target_y = waypoints(current_index, 2);
last_point = size(waypoints, 1);
target_theta = waypoints(current_index, 3);
target_theta = atan2(sin(target_theta), cos(target_theta));

end
CONTROL FUNCTION:
function [v, omega, next_index] = ComputeControl(target_x, target_y, obstacle, current_index, target_theta, last_point, current_x, current_y, x_ang, y_ang, z_ang, w_ang, ranges)

% Constants
max_velocity = 0.2; % max linear velocity
max_yaw_rate = 0.4; % max angular velocity
max_distance = 0.05; % max distance to consider waypoint reached
l = 640; % size of the camera’s image
h = 480;

% Initialize output
next_index = int32(current_index); % Initialize as integer (or the appropriate type)

% Coordinates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);

% Position and direction of the robot
current_angle = quat2eul([x_ang y_ang z_ang w_ang]);
yaw_angle = current_angle(3);
if yaw_angle > pi
current_theta = yaw_angle – 2*pi;
else
current_theta = yaw_angle;
end

% Compute distance and angle to the target waypoint
dx = target_x – current_x;
dy = target_y – current_y;
distance = sqrt(dx^2 + dy^2); % Distance to the waypoints
dist_obs = min(ranges); % Distance to the closest obstacle (Radar)
angle_to_target = atan2(dy, dx); % Angle needed to reach the waypoints

% Adjust the angle to be in the range [-pi, pi]
if dx < 0
if dy > 0
angle_to_target = angle_to_target + pi;
else
angle_to_target = angle_to_target – pi;
end
end

% Compute delta theta and the error in the direction
d_theta = target_theta – current_theta;
angle_error = current_theta – angle_to_target;

% Compute the control logic commands to achieve the waypoints and avoid the obstacles
if (x_obst – l/2) > 0
omega = max_yaw_rate;
v = max_velocity;
else
if current_index > last_point
v = 0;
omega = 0;
next_index = current_index;
else
if distance <= max_distance && abs(d_theta) <= 0.05
next_index = current_index + 1;
else
next_index = current_index; % Ensure next_index is assigned
end
if distance > max_distance
if abs(angle_error) > 0.01
if abs(angle_error) > 0.5
omega = max_yaw_rate;
elseif abs(angle_error) > 0.3 && abs(angle_error) <= 0.5
omega = 0.5 * max_yaw_rate;
else
omega = 0.1 * max_yaw_rate;
end
if current_theta > angle_to_target && current_index < 7
omega = -omega;
end
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
else
omega = 0;
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
end
else
if abs(d_theta) > 0.05
omega = max_yaw_rate * d_theta;
v = 0;
if current_theta > target_theta
omega = -omega;
end
else
omega = 0;
v = 0;
end
end
end
end

% Limit the velocities just in case
v = min(v, max_velocity);
omega = min(max(omega, -max_yaw_rate), max_yaw_rate);
endI am working on creating a model in Simulink that allows me to control a Turtlebot waffle pi so that it moves along a 6-point path. Along the path there will be obstacles in the form of red and green spheres. The objective is for the robot to reach all the points of the path avoiding the obstacles, if the sphere is red, avoid to the right and if it is green, avoid to the left.
I have already created the following Simulink model where the most important thing is in the control function since it describes the behavior of the robot, however the error that keeps appearing is the following: Error: Block ”Project_3/MATLAB Function” does not fully set the dimensions of output ‘next_index’. Which I do not find sense since the variable next_index is defined from the beginning. I attach the images of the model that I am creating.

function [area, x_obst, y_obst, target_x, target_y, obstacle, current_index, target_theta,last_point] = WaypointSelector(a, cent, waypoints, current_index)
%Extract obstacle’s area and position
[~,i] = max(a);
area = max(a);
if ~isempty(i)
obstacle = cent(i,:);
else
obstacle = [0,0];
end
% Cordanates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);
% Extract target waypoint
target_x = waypoints(current_index, 1);
target_y = waypoints(current_index, 2);
last_point = size(waypoints, 1);
target_theta = waypoints(current_index, 3);
target_theta = atan2(sin(target_theta), cos(target_theta));

end
CONTROL FUNCTION:
function [v, omega, next_index] = ComputeControl(target_x, target_y, obstacle, current_index, target_theta, last_point, current_x, current_y, x_ang, y_ang, z_ang, w_ang, ranges)

% Constants
max_velocity = 0.2; % max linear velocity
max_yaw_rate = 0.4; % max angular velocity
max_distance = 0.05; % max distance to consider waypoint reached
l = 640; % size of the camera’s image
h = 480;

% Initialize output
next_index = int32(current_index); % Initialize as integer (or the appropriate type)

% Coordinates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);

% Position and direction of the robot
current_angle = quat2eul([x_ang y_ang z_ang w_ang]);
yaw_angle = current_angle(3);
if yaw_angle > pi
current_theta = yaw_angle – 2*pi;
else
current_theta = yaw_angle;
end

% Compute distance and angle to the target waypoint
dx = target_x – current_x;
dy = target_y – current_y;
distance = sqrt(dx^2 + dy^2); % Distance to the waypoints
dist_obs = min(ranges); % Distance to the closest obstacle (Radar)
angle_to_target = atan2(dy, dx); % Angle needed to reach the waypoints

% Adjust the angle to be in the range [-pi, pi]
if dx < 0
if dy > 0
angle_to_target = angle_to_target + pi;
else
angle_to_target = angle_to_target – pi;
end
end

% Compute delta theta and the error in the direction
d_theta = target_theta – current_theta;
angle_error = current_theta – angle_to_target;

% Compute the control logic commands to achieve the waypoints and avoid the obstacles
if (x_obst – l/2) > 0
omega = max_yaw_rate;
v = max_velocity;
else
if current_index > last_point
v = 0;
omega = 0;
next_index = current_index;
else
if distance <= max_distance && abs(d_theta) <= 0.05
next_index = current_index + 1;
else
next_index = current_index; % Ensure next_index is assigned
end
if distance > max_distance
if abs(angle_error) > 0.01
if abs(angle_error) > 0.5
omega = max_yaw_rate;
elseif abs(angle_error) > 0.3 && abs(angle_error) <= 0.5
omega = 0.5 * max_yaw_rate;
else
omega = 0.1 * max_yaw_rate;
end
if current_theta > angle_to_target && current_index < 7
omega = -omega;
end
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
else
omega = 0;
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
end
else
if abs(d_theta) > 0.05
omega = max_yaw_rate * d_theta;
v = 0;
if current_theta > target_theta
omega = -omega;
end
else
omega = 0;
v = 0;
end
end
end
end

% Limit the velocities just in case
v = min(v, max_velocity);
omega = min(max(omega, -max_yaw_rate), max_yaw_rate);
end I am working on creating a model in Simulink that allows me to control a Turtlebot waffle pi so that it moves along a 6-point path. Along the path there will be obstacles in the form of red and green spheres. The objective is for the robot to reach all the points of the path avoiding the obstacles, if the sphere is red, avoid to the right and if it is green, avoid to the left.
I have already created the following Simulink model where the most important thing is in the control function since it describes the behavior of the robot, however the error that keeps appearing is the following: Error: Block ”Project_3/MATLAB Function” does not fully set the dimensions of output ‘next_index’. Which I do not find sense since the variable next_index is defined from the beginning. I attach the images of the model that I am creating.

function [area, x_obst, y_obst, target_x, target_y, obstacle, current_index, target_theta,last_point] = WaypointSelector(a, cent, waypoints, current_index)
%Extract obstacle’s area and position
[~,i] = max(a);
area = max(a);
if ~isempty(i)
obstacle = cent(i,:);
else
obstacle = [0,0];
end
% Cordanates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);
% Extract target waypoint
target_x = waypoints(current_index, 1);
target_y = waypoints(current_index, 2);
last_point = size(waypoints, 1);
target_theta = waypoints(current_index, 3);
target_theta = atan2(sin(target_theta), cos(target_theta));

end
CONTROL FUNCTION:
function [v, omega, next_index] = ComputeControl(target_x, target_y, obstacle, current_index, target_theta, last_point, current_x, current_y, x_ang, y_ang, z_ang, w_ang, ranges)

% Constants
max_velocity = 0.2; % max linear velocity
max_yaw_rate = 0.4; % max angular velocity
max_distance = 0.05; % max distance to consider waypoint reached
l = 640; % size of the camera’s image
h = 480;

% Initialize output
next_index = int32(current_index); % Initialize as integer (or the appropriate type)

% Coordinates of the obstacles
x_obst = obstacle(1);
y_obst = obstacle(2);

% Position and direction of the robot
current_angle = quat2eul([x_ang y_ang z_ang w_ang]);
yaw_angle = current_angle(3);
if yaw_angle > pi
current_theta = yaw_angle – 2*pi;
else
current_theta = yaw_angle;
end

% Compute distance and angle to the target waypoint
dx = target_x – current_x;
dy = target_y – current_y;
distance = sqrt(dx^2 + dy^2); % Distance to the waypoints
dist_obs = min(ranges); % Distance to the closest obstacle (Radar)
angle_to_target = atan2(dy, dx); % Angle needed to reach the waypoints

% Adjust the angle to be in the range [-pi, pi]
if dx < 0
if dy > 0
angle_to_target = angle_to_target + pi;
else
angle_to_target = angle_to_target – pi;
end
end

% Compute delta theta and the error in the direction
d_theta = target_theta – current_theta;
angle_error = current_theta – angle_to_target;

% Compute the control logic commands to achieve the waypoints and avoid the obstacles
if (x_obst – l/2) > 0
omega = max_yaw_rate;
v = max_velocity;
else
if current_index > last_point
v = 0;
omega = 0;
next_index = current_index;
else
if distance <= max_distance && abs(d_theta) <= 0.05
next_index = current_index + 1;
else
next_index = current_index; % Ensure next_index is assigned
end
if distance > max_distance
if abs(angle_error) > 0.01
if abs(angle_error) > 0.5
omega = max_yaw_rate;
elseif abs(angle_error) > 0.3 && abs(angle_error) <= 0.5
omega = 0.5 * max_yaw_rate;
else
omega = 0.1 * max_yaw_rate;
end
if current_theta > angle_to_target && current_index < 7
omega = -omega;
end
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
else
omega = 0;
if distance >= 3 * max_distance
v = max_velocity;
else
v = max_velocity * (distance / (distance + 1));
end
end
else
if abs(d_theta) > 0.05
omega = max_yaw_rate * d_theta;
v = 0;
if current_theta > target_theta
omega = -omega;
end
else
omega = 0;
v = 0;
end
end
end
end

% Limit the velocities just in case
v = min(v, max_velocity);
omega = min(max(omega, -max_yaw_rate), max_yaw_rate);
end simulink, turtlebot, matlab, control, gazebo, ros, image processing, motion, error MATLAB Answers — New Questions

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Hi
I have a list of string variables, which all ends with "_STI". How can I group them together so that I can perform the same operations to them. For example, I want to assign a number to all the variables ends with "_STI".
Thanks very muchHi
I have a list of string variables, which all ends with "_STI". How can I group them together so that I can perform the same operations to them. For example, I want to assign a number to all the variables ends with "_STI".
Thanks very much Hi
I have a list of string variables, which all ends with "_STI". How can I group them together so that I can perform the same operations to them. For example, I want to assign a number to all the variables ends with "_STI".
Thanks very much string identifier operation MATLAB Answers — New Questions

​

I am running a simulation of 100s of thousands loop and I am noticing that inside the each loop an all() function consumes almost 95% of the time. I want a faster alternate to this.
So here is my algorithm:
varname=rand([24665846,4])
for i=1:1000000
idx=idxkeep(i);
ind1=all(varname(:,1:4)==varname(idx,1:4),2);
ind=find(ind1);
endI am running a simulation of 100s of thousands loop and I am noticing that inside the each loop an all() function consumes almost 95% of the time. I want a faster alternate to this.
So here is my algorithm:
varname=rand([24665846,4])
for i=1:1000000
idx=idxkeep(i);
ind1=all(varname(:,1:4)==varname(idx,1:4),2);
ind=find(ind1);
end I am running a simulation of 100s of thousands loop and I am noticing that inside the each loop an all() function consumes almost 95% of the time. I want a faster alternate to this.
So here is my algorithm:
varname=rand([24665846,4])
for i=1:1000000
idx=idxkeep(i);
ind1=all(varname(:,1:4)==varname(idx,1:4),2);
ind=find(ind1);
end matlab, all() MATLAB Answers — New Questions

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