Please i am trying to make a time series with daily financial datas.
The datas are observed daily except on weekends.
My main concern is that i am trying to set a moving starting (02 of january 2017) date with the function dattetime but i am having an error message. Please could you tell me what i did wrong?
M
Also , can you tell me how i can account for the weekly two days break in the time series.

RegardsPlease i am trying to make a time series with daily financial datas.
The datas are observed daily except on weekends.
My main concern is that i am trying to set a moving starting (02 of january 2017) date with the function dattetime but i am having an error message. Please could you tell me what i did wrong?
M
Also , can you tell me how i can account for the weekly two days break in the time series.

Regards Please i am trying to make a time series with daily financial datas.
The datas are observed daily except on weekends.
My main concern is that i am trying to set a moving starting (02 of january 2017) date with the function dattetime but i am having an error message. Please could you tell me what i did wrong?
M
Also , can you tell me how i can account for the weekly two days break in the time series.

Regards daily time series MATLAB Answers — New Questions

​

I have imported a 3D CAD model of a quadcopter into Simulink Multibody and am working to connect the Simulink model to ArduPilot using SITL. To achieve this, I am using an S-Function block that is designed to send input data from Simulink to ArduPilot and receive output data from ArduPilot back into Simulink, forming a closed-loop system.

The model compiles and runs without errors, but it fails to establish a connection or communication with ArduPilot. When I hit the run button, the simulation starts immediately without waiting for ArduPilot to connect. I’m unable to identify why this is happening. The code for my S-Function is attached. Could someone please help me troubleshoot this issue?

#define S_FUNCTION_NAME sil_connector_new1
#define S_FUNCTION_LEVEL 2

#include "simstruc.h"
#include <iostream>
#include <winsock2.h>
#include <Ws2tcpip.h>
#include "C:/Users/tihan/Desktop/ardupilot/build/sitl/libraries/GCS_MAVLink/include/mavlink/v2.0/ardupilotmega/mavlink.h"

#pragma comment(lib, "ws2_32.lib")

#define SERVER_IP "127.0.0.1"
#define SERVER_PORT 5760

class UDPConnector {
public:
UDPConnector(const char* ip, int port) : server_ip(ip), server_port(port), sockfd(-1) {}

bool initialize() {
WSADATA wsaData;
if (WSAStartup(MAKEWORD(2, 2), &wsaData) != 0) {
std::cerr << "WSAStartup failed with error: " << WSAGetLastError() << std::endl;
return false;
}

sockfd = socket(AF_INET, SOCK_DGRAM, 0);
if (sockfd == INVALID_SOCKET) {
std::cerr << "Socket creation failed with error: " << WSAGetLastError() << std::endl;
return false;
}

memset(&server_addr, 0, sizeof(server_addr));
server_addr.sin_family = AF_INET;
server_addr.sin_port = htons(server_port);
server_addr.sin_addr.s_addr = inet_addr(server_ip);

// Try to connect to SITL
std::cout << "Waiting for ArduPilot SITL connection…" << std::endl;
for (int attempt = 0; attempt < 10; ++attempt) {
if (test_connection()) {
std::cout << "Connection established to ArduPilot SITL on " << server_ip << ":" << server_port << std::endl;
return true;
}
std::this_thread::sleep_for(std::chrono::seconds(1));
}

std::cerr << "Failed to establish connection to ArduPilot SITL." << std::endl;
return false;
}

bool send_message(const uint8_t* buffer, size_t length) {
if (sendto(sockfd, (const char*)buffer, length, 0, (struct sockaddr*)&server_addr, sizeof(server_addr)) == SOCKET_ERROR) {
std::cerr << "Failed to send message with error: " << WSAGetLastError() << std::endl;
return false;
}
return true;
}

~UDPConnector() {
if (sockfd != INVALID_SOCKET) {
closesocket(sockfd);
}
WSACleanup();
}

private:
const char* server_ip;
int server_port;
SOCKET sockfd;
struct sockaddr_in server_addr;

bool test_connection() {
mavlink_message_t msg;
uint8_t buf[MAVLINK_MAX_PACKET_LEN];

// Send a heartbeat message to test the connection
mavlink_msg_heartbeat_pack(1, 200, &msg, MAV_TYPE_ONBOARD_CONTROLLER, MAV_AUTOPILOT_INVALID, 0, 0, 0);
size_t len = mavlink_msg_to_send_buffer(buf, &msg);

if (!send_message(buf, len)) {
return false;
}

// Non-blocking receive to verify response
fd_set readfds;
FD_ZERO(&readfds);
FD_SET(sockfd, &readfds);

struct timeval timeout;
timeout.tv_sec = 1;
timeout.tv_usec = 0;

if (select(0, &readfds, NULL, NULL, &timeout) > 0) {
char recv_buf[1024];
int recv_len = recvfrom(sockfd, recv_buf, sizeof(recv_buf), 0, NULL, NULL);
if (recv_len > 0) {
std::cout << "Heartbeat received from SITL." << std::endl;
return true;
}
}

return false;
}
};

UDPConnector connector(SERVER_IP, SERVER_PORT);

void wait_for_ardupilot_connection(SimStruct *S) {
// Wait for connection with ArduPilot
if (!connector.initialize()) {
ssSetErrorStatus(S, "Unable to establish UDP connection to ArduPilot SITL.");
return;
}
}

void mdlInitializeSizes(SimStruct *S) {
ssSetNumInputPorts(S, 7); // 7 inputs: 6 vectors + 1 constant (time)
ssSetNumOutputPorts(S, 4); // 4 outputs for the 4 motor PWM signals

// 6 input ports for sensor data as [1×3] vectors
for (int i = 0; i < 6; ++i) { // 6 inputs for acceleration, gyro, position, velocity, attitude, magnetometer
ssSetInputPortWidth(S, i, 3); // Each sensor input is a [1×3] vector
ssSetInputPortDirectFeedThrough(S, i, 1); // Declare direct feedthrough
}

// Time input (constant scalar)
ssSetInputPortWidth(S, 6, 1); // Time as constant (scalar)
ssSetInputPortDirectFeedThrough(S, 6, 1); // Declare direct feedthrough for time input

// 4 output ports for motor PWM signals
for (int i = 0; i < 4; ++i) {
ssSetOutputPortWidth(S, i, 1); // Output for each motor PWM signal
}

ssSetNumSampleTimes(S, 1);
}

void mdlInitializeSampleTimes(SimStruct *S) {
ssSetSampleTime(S, 0, INHERITED_SAMPLE_TIME);
ssSetOffsetTime(S, 0, 0.0);
}

void mdlStart(SimStruct *S) {
// Initialize the UDP connection to ArduPilot SITL
wait_for_ardupilot_connection(S);
}

void send_mavlink_command(SimStruct *S, uint8_t command, float param1, float param2, float param3) {
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

// Construct the COMMAND_LONG message
mavlink_msg_command_long_pack(1, 200, &msg, 1, 1, command, 0, param1, param2, param3, 0, 0, 0, 0);

// Send the command to ArduPilot via UDP
uint16_t len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);
}

void mdlOutputs(SimStruct *S, int_T tid) {
const real_T *accel = ssGetInputPortRealSignal(S, 0); // [1×3] vector for acceleration
const real_T *gyro = ssGetInputPortRealSignal(S, 1); // [1×3] vector for gyro data
const real_T *position = ssGetInputPortRealSignal(S, 2); // [1×3] vector for position
const real_T *velocity = ssGetInputPortRealSignal(S, 3); // [1×3] vector for velocity
const real_T *attitude = ssGetInputPortRealSignal(S, 4); // [1×3] vector for attitude (phi, theta, psi)
const real_T *mag = ssGetInputPortRealSignal(S, 5); // [1×3] vector for magnetometer data
const real_T *timestamp = ssGetInputPortRealSignal(S, 6); // Scalar for time input (constant)

// Send a "Takeoff" command if requested
if (position[2] < 10.0) { // Check if altitude is below the desired takeoff height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_TAKEOFF, 0, 10.0, 0); // Takeoff to 10 meters altitude
}

// Send a "Land" command if requested
if (position[2] > 10.0) { // Check if altitude is above the desired landing height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_LAND, 0, 0, 0); // Land at current location
}

// Send PWM control data to ArduPilot for four motors (adjust as needed)
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

uint16_t len = mavlink_msg_scaled_imu_pack(1, 200, &msg,
static_cast<uint32_t>(*timestamp),
static_cast<int16_t>(accel[0] * 1000), static_cast<int16_t>(accel[1] * 1000), static_cast<int16_t>(accel[2] * 1000),
static_cast<int16_t>(gyro[0] * 1000), static_cast<int16_t>(gyro[1] * 1000), static_cast<int16_t>(gyro[2] * 1000),
static_cast<int16_t>(mag[0] * 1000), static_cast<int16_t>(mag[1] * 1000), static_cast<int16_t>(mag[2] * 1000),
0); // Default temperature value of 0

len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);

// Receive PWM signals for all four motors from ArduPilot
int pwm_signal[4] = {0, 0, 0, 0}; // Array to hold PWM signals for four motors
int ret = recvfrom(connector.sockfd, (char *)pwm_signal, sizeof(pwm_signal), 0, NULL, NULL);

if (ret > 0) {
real_T *output_pwm1 = ssGetOutputPortRealSignal(S, 0);
real_T *output_pwm2 = ssGetOutputPortRealSignal(S, 1);
real_T *output_pwm3 = ssGetOutputPortRealSignal(S, 2);
real_T *output_pwm4 = ssGetOutputPortRealSignal(S, 3);

// Map PWM signals for each motor to angular velocities
double min_pwm = 1000.0;
double max_pwm = 2000.0;
double min_angular_velocity = 0.0; // Minimum angular velocity (0 rad/s)
double max_angular_velocity = 10.0; // Maximum angular velocity (10 rad/s)

// Map each PWM signal to an angular velocity
*output_pwm1 = min_angular_velocity + (pwm_signal[0] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm2 = min_angular_velocity + (pwm_signal[1] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm3 = min_angular_velocity + (pwm_signal[2] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm4 = min_angular_velocity + (pwm_signal[3] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
}
}

void mdlTerminate(SimStruct *S) {
connector.~UDPConnector();
}

#ifdef MATLAB_MEX_FILE
#include "simulink.c"
#else
#include "cg_sfun.h"
#endifI have imported a 3D CAD model of a quadcopter into Simulink Multibody and am working to connect the Simulink model to ArduPilot using SITL. To achieve this, I am using an S-Function block that is designed to send input data from Simulink to ArduPilot and receive output data from ArduPilot back into Simulink, forming a closed-loop system.

The model compiles and runs without errors, but it fails to establish a connection or communication with ArduPilot. When I hit the run button, the simulation starts immediately without waiting for ArduPilot to connect. I’m unable to identify why this is happening. The code for my S-Function is attached. Could someone please help me troubleshoot this issue?

#define S_FUNCTION_NAME sil_connector_new1
#define S_FUNCTION_LEVEL 2

#include "simstruc.h"
#include <iostream>
#include <winsock2.h>
#include <Ws2tcpip.h>
#include "C:/Users/tihan/Desktop/ardupilot/build/sitl/libraries/GCS_MAVLink/include/mavlink/v2.0/ardupilotmega/mavlink.h"

#pragma comment(lib, "ws2_32.lib")

#define SERVER_IP "127.0.0.1"
#define SERVER_PORT 5760

class UDPConnector {
public:
UDPConnector(const char* ip, int port) : server_ip(ip), server_port(port), sockfd(-1) {}

bool initialize() {
WSADATA wsaData;
if (WSAStartup(MAKEWORD(2, 2), &wsaData) != 0) {
std::cerr << "WSAStartup failed with error: " << WSAGetLastError() << std::endl;
return false;
}

sockfd = socket(AF_INET, SOCK_DGRAM, 0);
if (sockfd == INVALID_SOCKET) {
std::cerr << "Socket creation failed with error: " << WSAGetLastError() << std::endl;
return false;
}

memset(&server_addr, 0, sizeof(server_addr));
server_addr.sin_family = AF_INET;
server_addr.sin_port = htons(server_port);
server_addr.sin_addr.s_addr = inet_addr(server_ip);

// Try to connect to SITL
std::cout << "Waiting for ArduPilot SITL connection…" << std::endl;
for (int attempt = 0; attempt < 10; ++attempt) {
if (test_connection()) {
std::cout << "Connection established to ArduPilot SITL on " << server_ip << ":" << server_port << std::endl;
return true;
}
std::this_thread::sleep_for(std::chrono::seconds(1));
}

std::cerr << "Failed to establish connection to ArduPilot SITL." << std::endl;
return false;
}

bool send_message(const uint8_t* buffer, size_t length) {
if (sendto(sockfd, (const char*)buffer, length, 0, (struct sockaddr*)&server_addr, sizeof(server_addr)) == SOCKET_ERROR) {
std::cerr << "Failed to send message with error: " << WSAGetLastError() << std::endl;
return false;
}
return true;
}

~UDPConnector() {
if (sockfd != INVALID_SOCKET) {
closesocket(sockfd);
}
WSACleanup();
}

private:
const char* server_ip;
int server_port;
SOCKET sockfd;
struct sockaddr_in server_addr;

bool test_connection() {
mavlink_message_t msg;
uint8_t buf[MAVLINK_MAX_PACKET_LEN];

// Send a heartbeat message to test the connection
mavlink_msg_heartbeat_pack(1, 200, &msg, MAV_TYPE_ONBOARD_CONTROLLER, MAV_AUTOPILOT_INVALID, 0, 0, 0);
size_t len = mavlink_msg_to_send_buffer(buf, &msg);

if (!send_message(buf, len)) {
return false;
}

// Non-blocking receive to verify response
fd_set readfds;
FD_ZERO(&readfds);
FD_SET(sockfd, &readfds);

struct timeval timeout;
timeout.tv_sec = 1;
timeout.tv_usec = 0;

if (select(0, &readfds, NULL, NULL, &timeout) > 0) {
char recv_buf[1024];
int recv_len = recvfrom(sockfd, recv_buf, sizeof(recv_buf), 0, NULL, NULL);
if (recv_len > 0) {
std::cout << "Heartbeat received from SITL." << std::endl;
return true;
}
}

return false;
}
};

UDPConnector connector(SERVER_IP, SERVER_PORT);

void wait_for_ardupilot_connection(SimStruct *S) {
// Wait for connection with ArduPilot
if (!connector.initialize()) {
ssSetErrorStatus(S, "Unable to establish UDP connection to ArduPilot SITL.");
return;
}
}

void mdlInitializeSizes(SimStruct *S) {
ssSetNumInputPorts(S, 7); // 7 inputs: 6 vectors + 1 constant (time)
ssSetNumOutputPorts(S, 4); // 4 outputs for the 4 motor PWM signals

// 6 input ports for sensor data as [1×3] vectors
for (int i = 0; i < 6; ++i) { // 6 inputs for acceleration, gyro, position, velocity, attitude, magnetometer
ssSetInputPortWidth(S, i, 3); // Each sensor input is a [1×3] vector
ssSetInputPortDirectFeedThrough(S, i, 1); // Declare direct feedthrough
}

// Time input (constant scalar)
ssSetInputPortWidth(S, 6, 1); // Time as constant (scalar)
ssSetInputPortDirectFeedThrough(S, 6, 1); // Declare direct feedthrough for time input

// 4 output ports for motor PWM signals
for (int i = 0; i < 4; ++i) {
ssSetOutputPortWidth(S, i, 1); // Output for each motor PWM signal
}

ssSetNumSampleTimes(S, 1);
}

void mdlInitializeSampleTimes(SimStruct *S) {
ssSetSampleTime(S, 0, INHERITED_SAMPLE_TIME);
ssSetOffsetTime(S, 0, 0.0);
}

void mdlStart(SimStruct *S) {
// Initialize the UDP connection to ArduPilot SITL
wait_for_ardupilot_connection(S);
}

void send_mavlink_command(SimStruct *S, uint8_t command, float param1, float param2, float param3) {
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

// Construct the COMMAND_LONG message
mavlink_msg_command_long_pack(1, 200, &msg, 1, 1, command, 0, param1, param2, param3, 0, 0, 0, 0);

// Send the command to ArduPilot via UDP
uint16_t len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);
}

void mdlOutputs(SimStruct *S, int_T tid) {
const real_T *accel = ssGetInputPortRealSignal(S, 0); // [1×3] vector for acceleration
const real_T *gyro = ssGetInputPortRealSignal(S, 1); // [1×3] vector for gyro data
const real_T *position = ssGetInputPortRealSignal(S, 2); // [1×3] vector for position
const real_T *velocity = ssGetInputPortRealSignal(S, 3); // [1×3] vector for velocity
const real_T *attitude = ssGetInputPortRealSignal(S, 4); // [1×3] vector for attitude (phi, theta, psi)
const real_T *mag = ssGetInputPortRealSignal(S, 5); // [1×3] vector for magnetometer data
const real_T *timestamp = ssGetInputPortRealSignal(S, 6); // Scalar for time input (constant)

// Send a "Takeoff" command if requested
if (position[2] < 10.0) { // Check if altitude is below the desired takeoff height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_TAKEOFF, 0, 10.0, 0); // Takeoff to 10 meters altitude
}

// Send a "Land" command if requested
if (position[2] > 10.0) { // Check if altitude is above the desired landing height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_LAND, 0, 0, 0); // Land at current location
}

// Send PWM control data to ArduPilot for four motors (adjust as needed)
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

uint16_t len = mavlink_msg_scaled_imu_pack(1, 200, &msg,
static_cast<uint32_t>(*timestamp),
static_cast<int16_t>(accel[0] * 1000), static_cast<int16_t>(accel[1] * 1000), static_cast<int16_t>(accel[2] * 1000),
static_cast<int16_t>(gyro[0] * 1000), static_cast<int16_t>(gyro[1] * 1000), static_cast<int16_t>(gyro[2] * 1000),
static_cast<int16_t>(mag[0] * 1000), static_cast<int16_t>(mag[1] * 1000), static_cast<int16_t>(mag[2] * 1000),
0); // Default temperature value of 0

len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);

// Receive PWM signals for all four motors from ArduPilot
int pwm_signal[4] = {0, 0, 0, 0}; // Array to hold PWM signals for four motors
int ret = recvfrom(connector.sockfd, (char *)pwm_signal, sizeof(pwm_signal), 0, NULL, NULL);

if (ret > 0) {
real_T *output_pwm1 = ssGetOutputPortRealSignal(S, 0);
real_T *output_pwm2 = ssGetOutputPortRealSignal(S, 1);
real_T *output_pwm3 = ssGetOutputPortRealSignal(S, 2);
real_T *output_pwm4 = ssGetOutputPortRealSignal(S, 3);

// Map PWM signals for each motor to angular velocities
double min_pwm = 1000.0;
double max_pwm = 2000.0;
double min_angular_velocity = 0.0; // Minimum angular velocity (0 rad/s)
double max_angular_velocity = 10.0; // Maximum angular velocity (10 rad/s)

// Map each PWM signal to an angular velocity
*output_pwm1 = min_angular_velocity + (pwm_signal[0] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm2 = min_angular_velocity + (pwm_signal[1] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm3 = min_angular_velocity + (pwm_signal[2] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm4 = min_angular_velocity + (pwm_signal[3] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
}
}

void mdlTerminate(SimStruct *S) {
connector.~UDPConnector();
}

#ifdef MATLAB_MEX_FILE
#include "simulink.c"
#else
#include "cg_sfun.h"
#endif I have imported a 3D CAD model of a quadcopter into Simulink Multibody and am working to connect the Simulink model to ArduPilot using SITL. To achieve this, I am using an S-Function block that is designed to send input data from Simulink to ArduPilot and receive output data from ArduPilot back into Simulink, forming a closed-loop system.

The model compiles and runs without errors, but it fails to establish a connection or communication with ArduPilot. When I hit the run button, the simulation starts immediately without waiting for ArduPilot to connect. I’m unable to identify why this is happening. The code for my S-Function is attached. Could someone please help me troubleshoot this issue?

#define S_FUNCTION_NAME sil_connector_new1
#define S_FUNCTION_LEVEL 2

#include "simstruc.h"
#include <iostream>
#include <winsock2.h>
#include <Ws2tcpip.h>
#include "C:/Users/tihan/Desktop/ardupilot/build/sitl/libraries/GCS_MAVLink/include/mavlink/v2.0/ardupilotmega/mavlink.h"

#pragma comment(lib, "ws2_32.lib")

#define SERVER_IP "127.0.0.1"
#define SERVER_PORT 5760

class UDPConnector {
public:
UDPConnector(const char* ip, int port) : server_ip(ip), server_port(port), sockfd(-1) {}

bool initialize() {
WSADATA wsaData;
if (WSAStartup(MAKEWORD(2, 2), &wsaData) != 0) {
std::cerr << "WSAStartup failed with error: " << WSAGetLastError() << std::endl;
return false;
}

sockfd = socket(AF_INET, SOCK_DGRAM, 0);
if (sockfd == INVALID_SOCKET) {
std::cerr << "Socket creation failed with error: " << WSAGetLastError() << std::endl;
return false;
}

memset(&server_addr, 0, sizeof(server_addr));
server_addr.sin_family = AF_INET;
server_addr.sin_port = htons(server_port);
server_addr.sin_addr.s_addr = inet_addr(server_ip);

// Try to connect to SITL
std::cout << "Waiting for ArduPilot SITL connection…" << std::endl;
for (int attempt = 0; attempt < 10; ++attempt) {
if (test_connection()) {
std::cout << "Connection established to ArduPilot SITL on " << server_ip << ":" << server_port << std::endl;
return true;
}
std::this_thread::sleep_for(std::chrono::seconds(1));
}

std::cerr << "Failed to establish connection to ArduPilot SITL." << std::endl;
return false;
}

bool send_message(const uint8_t* buffer, size_t length) {
if (sendto(sockfd, (const char*)buffer, length, 0, (struct sockaddr*)&server_addr, sizeof(server_addr)) == SOCKET_ERROR) {
std::cerr << "Failed to send message with error: " << WSAGetLastError() << std::endl;
return false;
}
return true;
}

~UDPConnector() {
if (sockfd != INVALID_SOCKET) {
closesocket(sockfd);
}
WSACleanup();
}

private:
const char* server_ip;
int server_port;
SOCKET sockfd;
struct sockaddr_in server_addr;

bool test_connection() {
mavlink_message_t msg;
uint8_t buf[MAVLINK_MAX_PACKET_LEN];

// Send a heartbeat message to test the connection
mavlink_msg_heartbeat_pack(1, 200, &msg, MAV_TYPE_ONBOARD_CONTROLLER, MAV_AUTOPILOT_INVALID, 0, 0, 0);
size_t len = mavlink_msg_to_send_buffer(buf, &msg);

if (!send_message(buf, len)) {
return false;
}

// Non-blocking receive to verify response
fd_set readfds;
FD_ZERO(&readfds);
FD_SET(sockfd, &readfds);

struct timeval timeout;
timeout.tv_sec = 1;
timeout.tv_usec = 0;

if (select(0, &readfds, NULL, NULL, &timeout) > 0) {
char recv_buf[1024];
int recv_len = recvfrom(sockfd, recv_buf, sizeof(recv_buf), 0, NULL, NULL);
if (recv_len > 0) {
std::cout << "Heartbeat received from SITL." << std::endl;
return true;
}
}

return false;
}
};

UDPConnector connector(SERVER_IP, SERVER_PORT);

void wait_for_ardupilot_connection(SimStruct *S) {
// Wait for connection with ArduPilot
if (!connector.initialize()) {
ssSetErrorStatus(S, "Unable to establish UDP connection to ArduPilot SITL.");
return;
}
}

void mdlInitializeSizes(SimStruct *S) {
ssSetNumInputPorts(S, 7); // 7 inputs: 6 vectors + 1 constant (time)
ssSetNumOutputPorts(S, 4); // 4 outputs for the 4 motor PWM signals

// 6 input ports for sensor data as [1×3] vectors
for (int i = 0; i < 6; ++i) { // 6 inputs for acceleration, gyro, position, velocity, attitude, magnetometer
ssSetInputPortWidth(S, i, 3); // Each sensor input is a [1×3] vector
ssSetInputPortDirectFeedThrough(S, i, 1); // Declare direct feedthrough
}

// Time input (constant scalar)
ssSetInputPortWidth(S, 6, 1); // Time as constant (scalar)
ssSetInputPortDirectFeedThrough(S, 6, 1); // Declare direct feedthrough for time input

// 4 output ports for motor PWM signals
for (int i = 0; i < 4; ++i) {
ssSetOutputPortWidth(S, i, 1); // Output for each motor PWM signal
}

ssSetNumSampleTimes(S, 1);
}

void mdlInitializeSampleTimes(SimStruct *S) {
ssSetSampleTime(S, 0, INHERITED_SAMPLE_TIME);
ssSetOffsetTime(S, 0, 0.0);
}

void mdlStart(SimStruct *S) {
// Initialize the UDP connection to ArduPilot SITL
wait_for_ardupilot_connection(S);
}

void send_mavlink_command(SimStruct *S, uint8_t command, float param1, float param2, float param3) {
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

// Construct the COMMAND_LONG message
mavlink_msg_command_long_pack(1, 200, &msg, 1, 1, command, 0, param1, param2, param3, 0, 0, 0, 0);

// Send the command to ArduPilot via UDP
uint16_t len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);
}

void mdlOutputs(SimStruct *S, int_T tid) {
const real_T *accel = ssGetInputPortRealSignal(S, 0); // [1×3] vector for acceleration
const real_T *gyro = ssGetInputPortRealSignal(S, 1); // [1×3] vector for gyro data
const real_T *position = ssGetInputPortRealSignal(S, 2); // [1×3] vector for position
const real_T *velocity = ssGetInputPortRealSignal(S, 3); // [1×3] vector for velocity
const real_T *attitude = ssGetInputPortRealSignal(S, 4); // [1×3] vector for attitude (phi, theta, psi)
const real_T *mag = ssGetInputPortRealSignal(S, 5); // [1×3] vector for magnetometer data
const real_T *timestamp = ssGetInputPortRealSignal(S, 6); // Scalar for time input (constant)

// Send a "Takeoff" command if requested
if (position[2] < 10.0) { // Check if altitude is below the desired takeoff height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_TAKEOFF, 0, 10.0, 0); // Takeoff to 10 meters altitude
}

// Send a "Land" command if requested
if (position[2] > 10.0) { // Check if altitude is above the desired landing height (e.g., 10m)
send_mavlink_command(S, MAV_CMD_NAV_LAND, 0, 0, 0); // Land at current location
}

// Send PWM control data to ArduPilot for four motors (adjust as needed)
mavlink_message_t msg;
uint8_t buffer[MAVLINK_MAX_PACKET_LEN];

uint16_t len = mavlink_msg_scaled_imu_pack(1, 200, &msg,
static_cast<uint32_t>(*timestamp),
static_cast<int16_t>(accel[0] * 1000), static_cast<int16_t>(accel[1] * 1000), static_cast<int16_t>(accel[2] * 1000),
static_cast<int16_t>(gyro[0] * 1000), static_cast<int16_t>(gyro[1] * 1000), static_cast<int16_t>(gyro[2] * 1000),
static_cast<int16_t>(mag[0] * 1000), static_cast<int16_t>(mag[1] * 1000), static_cast<int16_t>(mag[2] * 1000),
0); // Default temperature value of 0

len = mavlink_msg_to_send_buffer(buffer, &msg);
connector.send_message(buffer, len);

// Receive PWM signals for all four motors from ArduPilot
int pwm_signal[4] = {0, 0, 0, 0}; // Array to hold PWM signals for four motors
int ret = recvfrom(connector.sockfd, (char *)pwm_signal, sizeof(pwm_signal), 0, NULL, NULL);

if (ret > 0) {
real_T *output_pwm1 = ssGetOutputPortRealSignal(S, 0);
real_T *output_pwm2 = ssGetOutputPortRealSignal(S, 1);
real_T *output_pwm3 = ssGetOutputPortRealSignal(S, 2);
real_T *output_pwm4 = ssGetOutputPortRealSignal(S, 3);

// Map PWM signals for each motor to angular velocities
double min_pwm = 1000.0;
double max_pwm = 2000.0;
double min_angular_velocity = 0.0; // Minimum angular velocity (0 rad/s)
double max_angular_velocity = 10.0; // Maximum angular velocity (10 rad/s)

// Map each PWM signal to an angular velocity
*output_pwm1 = min_angular_velocity + (pwm_signal[0] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm2 = min_angular_velocity + (pwm_signal[1] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm3 = min_angular_velocity + (pwm_signal[2] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
*output_pwm4 = min_angular_velocity + (pwm_signal[3] – min_pwm) * (max_angular_velocity – min_angular_velocity) / (max_pwm – min_pwm);
}
}

void mdlTerminate(SimStruct *S) {
connector.~UDPConnector();
}

#ifdef MATLAB_MEX_FILE
#include "simulink.c"
#else
#include "cg_sfun.h"
#endif initialization, simulink model, ardupilot, s function block, sitl, connection, communicationissue MATLAB Answers — New Questions

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I need to implement a real time FFT of the signal in the attached simulink model in order to detect the frequency and phase of the highest peak (it’s a single sinusoid, so it shouldn’t be an issue). As you can see, I’ve set the simulation step to 1/48000. I would like the detection update rate to be 40Hz, so the FFT is run 40 times a second. I’d like the FFT to be run on the newest samples (i.e. 48000/40) plus an overlap of 50% of the previous set (48000/80), so in other words, the latest 1800 samples. I’d like to zero pad this up to the next power of 2.
I was trying to figure out how to do a FIFO buffer that saves the last 1800 samples, but I couldn’t figure that out, and I couldn’t advance past that stage.
In case it helps, here’s what I have:
Simulink Version 24.2 (R2024b)
Control System Toolbox Version 24.2 (R2024b)
DSP System Toolbox Version 24.2 (R2024b)
Optimization Toolbox Version 24.2 (R2024b)
Signal Processing Toolbox Version 24.2 (R2024b)
Stateflow Version 24.2 (R2024b)
Statistics and Machine Learning Toolbox Version 24.2 (R2024b)
Thanks in advance
-BastianI need to implement a real time FFT of the signal in the attached simulink model in order to detect the frequency and phase of the highest peak (it’s a single sinusoid, so it shouldn’t be an issue). As you can see, I’ve set the simulation step to 1/48000. I would like the detection update rate to be 40Hz, so the FFT is run 40 times a second. I’d like the FFT to be run on the newest samples (i.e. 48000/40) plus an overlap of 50% of the previous set (48000/80), so in other words, the latest 1800 samples. I’d like to zero pad this up to the next power of 2.
I was trying to figure out how to do a FIFO buffer that saves the last 1800 samples, but I couldn’t figure that out, and I couldn’t advance past that stage.
In case it helps, here’s what I have:
Simulink Version 24.2 (R2024b)
Control System Toolbox Version 24.2 (R2024b)
DSP System Toolbox Version 24.2 (R2024b)
Optimization Toolbox Version 24.2 (R2024b)
Signal Processing Toolbox Version 24.2 (R2024b)
Stateflow Version 24.2 (R2024b)
Statistics and Machine Learning Toolbox Version 24.2 (R2024b)
Thanks in advance
-Bastian I need to implement a real time FFT of the signal in the attached simulink model in order to detect the frequency and phase of the highest peak (it’s a single sinusoid, so it shouldn’t be an issue). As you can see, I’ve set the simulation step to 1/48000. I would like the detection update rate to be 40Hz, so the FFT is run 40 times a second. I’d like the FFT to be run on the newest samples (i.e. 48000/40) plus an overlap of 50% of the previous set (48000/80), so in other words, the latest 1800 samples. I’d like to zero pad this up to the next power of 2.
I was trying to figure out how to do a FIFO buffer that saves the last 1800 samples, but I couldn’t figure that out, and I couldn’t advance past that stage.
In case it helps, here’s what I have:
Simulink Version 24.2 (R2024b)
Control System Toolbox Version 24.2 (R2024b)
DSP System Toolbox Version 24.2 (R2024b)
Optimization Toolbox Version 24.2 (R2024b)
Signal Processing Toolbox Version 24.2 (R2024b)
Stateflow Version 24.2 (R2024b)
Statistics and Machine Learning Toolbox Version 24.2 (R2024b)
Thanks in advance
-Bastian fft MATLAB Answers — New Questions

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The Matlab example "Landing a Vehicle Using Multistage Nonlinear MPC" (which can be found here), uses a multistage nonlinear MPC to perform the trajectory optimization and another multistage nonlinear MPC to do the motion control. In the script, the former is called the "planner" and the latter is called the "lander". My question is purely regarding the planner:
Why does the objective cost increase when the prediction horizon (p) increases?

Given the sample time Ts and prediction horizon p, the prediction time becomes Ts*p. Here are three configurations with their output from the fmincon() function that resides in the nlmpcmove() function. Except the values for Ts and p, all code is similar to the Matlab example given here.
Ts = 0.2; pPlanner = 45; leads to Objective cost = 445.5349
Ts = 0.2; pPlanner = 50; leads to Objective cost = 492.9689
Ts = 0.2; pPlanner = 55; leads to Objective cost = 541.1668
To my understanding, a larger prediction horizon should give room to a more optimized result. Suppose the ideal trajectory takes Ts*p = 0.2*45 = 9 seconds. Why would the configuration with 50 seconds not lead to the exact same results?
The answers is probably related to how the nlmpcmove() function uses the user provided cost function and terminal state to converge to a solution. What is the math behind this convergence?

I’m using Matlab R2021b. Related Toolboxes are: Model Predictive Control Toolbox and Optimization Toolbox.The Matlab example "Landing a Vehicle Using Multistage Nonlinear MPC" (which can be found here), uses a multistage nonlinear MPC to perform the trajectory optimization and another multistage nonlinear MPC to do the motion control. In the script, the former is called the "planner" and the latter is called the "lander". My question is purely regarding the planner:
Why does the objective cost increase when the prediction horizon (p) increases?

Given the sample time Ts and prediction horizon p, the prediction time becomes Ts*p. Here are three configurations with their output from the fmincon() function that resides in the nlmpcmove() function. Except the values for Ts and p, all code is similar to the Matlab example given here.
Ts = 0.2; pPlanner = 45; leads to Objective cost = 445.5349
Ts = 0.2; pPlanner = 50; leads to Objective cost = 492.9689
Ts = 0.2; pPlanner = 55; leads to Objective cost = 541.1668
To my understanding, a larger prediction horizon should give room to a more optimized result. Suppose the ideal trajectory takes Ts*p = 0.2*45 = 9 seconds. Why would the configuration with 50 seconds not lead to the exact same results?
The answers is probably related to how the nlmpcmove() function uses the user provided cost function and terminal state to converge to a solution. What is the math behind this convergence?

I’m using Matlab R2021b. Related Toolboxes are: Model Predictive Control Toolbox and Optimization Toolbox. The Matlab example "Landing a Vehicle Using Multistage Nonlinear MPC" (which can be found here), uses a multistage nonlinear MPC to perform the trajectory optimization and another multistage nonlinear MPC to do the motion control. In the script, the former is called the "planner" and the latter is called the "lander". My question is purely regarding the planner:
Why does the objective cost increase when the prediction horizon (p) increases?

Given the sample time Ts and prediction horizon p, the prediction time becomes Ts*p. Here are three configurations with their output from the fmincon() function that resides in the nlmpcmove() function. Except the values for Ts and p, all code is similar to the Matlab example given here.
Ts = 0.2; pPlanner = 45; leads to Objective cost = 445.5349
Ts = 0.2; pPlanner = 50; leads to Objective cost = 492.9689
Ts = 0.2; pPlanner = 55; leads to Objective cost = 541.1668
To my understanding, a larger prediction horizon should give room to a more optimized result. Suppose the ideal trajectory takes Ts*p = 0.2*45 = 9 seconds. Why would the configuration with 50 seconds not lead to the exact same results?
The answers is probably related to how the nlmpcmove() function uses the user provided cost function and terminal state to converge to a solution. What is the math behind this convergence?

I’m using Matlab R2021b. Related Toolboxes are: Model Predictive Control Toolbox and Optimization Toolbox. multistage nonlinear model predictive controller, landing rocket with mpc example MATLAB Answers — New Questions

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So, I have been modelling a EV model based of an article about the Bolt EV using simscape and I got a relatively ok model using the dc motor, but when trying to implement the PMSM I could not get good results from it, with weird torque and current responses. I do not have access to specifics parameters of the PMSM, what makes me suspect that it is the problem, but I am not sure how to estimate that with no access to the hardware to empiracally test it.So, I have been modelling a EV model based of an article about the Bolt EV using simscape and I got a relatively ok model using the dc motor, but when trying to implement the PMSM I could not get good results from it, with weird torque and current responses. I do not have access to specifics parameters of the PMSM, what makes me suspect that it is the problem, but I am not sure how to estimate that with no access to the hardware to empiracally test it. So, I have been modelling a EV model based of an article about the Bolt EV using simscape and I got a relatively ok model using the dc motor, but when trying to implement the PMSM I could not get good results from it, with weird torque and current responses. I do not have access to specifics parameters of the PMSM, what makes me suspect that it is the problem, but I am not sure how to estimate that with no access to the hardware to empiracally test it. simscape, simulink, electric_motor_control MATLAB Answers — New Questions

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Hello Everyone,
I have been trying to follow the example model "PMSM Velocity Control" where my final objective is to replace the idela converter with parameterized discrete devices. For now, I am using ideal converter, with different reference speed (Drive Cycle, constant, signal editor) and I have tuned the speed and current loops accordingly.
The Sample Time
Control Sample time (TSc) = Tsw/250 (Switching time over 250 samples per switching time)
PWM Sample time (TS) = 1/(10*fsw)
The motor is seem to follow the reference speed correctly, however the generated agte signals are seem to sampled sine wave, between 1 and -1.
The voltage (Phase-phase) and (Phase-to-Nuetral) waveform is quite unusual (my input is 48V)
Although the control loops are tuned and there is very low oscillation in the controlled output, however the phase current has hige distortion which I tried to suppress via low-pass filter.
When I put the parameterized semicondcutor instead of idela converter, the gate are signal are not even generating. A gate driver is used to provide PWM signal form the controller to the N-channel MOSFET.
I am attaching few screenshots and my model, if any could validate the model and provide the guidance regarding aforementioned.
Thank You!Hello Everyone,
I have been trying to follow the example model "PMSM Velocity Control" where my final objective is to replace the idela converter with parameterized discrete devices. For now, I am using ideal converter, with different reference speed (Drive Cycle, constant, signal editor) and I have tuned the speed and current loops accordingly.
The Sample Time
Control Sample time (TSc) = Tsw/250 (Switching time over 250 samples per switching time)
PWM Sample time (TS) = 1/(10*fsw)
The motor is seem to follow the reference speed correctly, however the generated agte signals are seem to sampled sine wave, between 1 and -1.
The voltage (Phase-phase) and (Phase-to-Nuetral) waveform is quite unusual (my input is 48V)
Although the control loops are tuned and there is very low oscillation in the controlled output, however the phase current has hige distortion which I tried to suppress via low-pass filter.
When I put the parameterized semicondcutor instead of idela converter, the gate are signal are not even generating. A gate driver is used to provide PWM signal form the controller to the N-channel MOSFET.
I am attaching few screenshots and my model, if any could validate the model and provide the guidance regarding aforementioned.
Thank You! Hello Everyone,
I have been trying to follow the example model "PMSM Velocity Control" where my final objective is to replace the idela converter with parameterized discrete devices. For now, I am using ideal converter, with different reference speed (Drive Cycle, constant, signal editor) and I have tuned the speed and current loops accordingly.
The Sample Time
Control Sample time (TSc) = Tsw/250 (Switching time over 250 samples per switching time)
PWM Sample time (TS) = 1/(10*fsw)
The motor is seem to follow the reference speed correctly, however the generated agte signals are seem to sampled sine wave, between 1 and -1.
The voltage (Phase-phase) and (Phase-to-Nuetral) waveform is quite unusual (my input is 48V)
Although the control loops are tuned and there is very low oscillation in the controlled output, however the phase current has hige distortion which I tried to suppress via low-pass filter.
When I put the parameterized semicondcutor instead of idela converter, the gate are signal are not even generating. A gate driver is used to provide PWM signal form the controller to the N-channel MOSFET.
I am attaching few screenshots and my model, if any could validate the model and provide the guidance regarding aforementioned.
Thank You! simscape, power_electronics_control MATLAB Answers — New Questions

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I want to use PID controller in Stateflow. I made two options (above): Simulink function and Simulink state.
How to use Matlab function, PID from Control System toolbox? This PID is object like transfer function, and I need time series.I want to use PID controller in Stateflow. I made two options (above): Simulink function and Simulink state.
How to use Matlab function, PID from Control System toolbox? This PID is object like transfer function, and I need time series. I want to use PID controller in Stateflow. I made two options (above): Simulink function and Simulink state.
How to use Matlab function, PID from Control System toolbox? This PID is object like transfer function, and I need time series. pid, stateflow, embedded matlab function MATLAB Answers — New Questions

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load flow bus blockload flow bus block load flow bus block load flow bus MATLAB Answers — New Questions

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I am using the los2() function to evaluate line-of-sight between two points. The function indicates that line-of-sight is lost when the elevation of the second point in the AER frame centered on the first point is greater than zero; point values corresponding to an elevation of zero are indicated as being below the horizon.
As far as I understand, all points at or above zero elevation at a particular location should be within line-of-sight from that location; however, this does not appear to agree with the results from los2. Is my understanding of the LOS calculation inaccurate or am I missing something about the way los2 performs its calculation?I am using the los2() function to evaluate line-of-sight between two points. The function indicates that line-of-sight is lost when the elevation of the second point in the AER frame centered on the first point is greater than zero; point values corresponding to an elevation of zero are indicated as being below the horizon.
As far as I understand, all points at or above zero elevation at a particular location should be within line-of-sight from that location; however, this does not appear to agree with the results from los2. Is my understanding of the LOS calculation inaccurate or am I missing something about the way los2 performs its calculation? I am using the los2() function to evaluate line-of-sight between two points. The function indicates that line-of-sight is lost when the elevation of the second point in the AER frame centered on the first point is greater than zero; point values corresponding to an elevation of zero are indicated as being below the horizon.
As far as I understand, all points at or above zero elevation at a particular location should be within line-of-sight from that location; however, this does not appear to agree with the results from los2. Is my understanding of the LOS calculation inaccurate or am I missing something about the way los2 performs its calculation? mapping toolbox, line of sight, los2, earth curvature MATLAB Answers — New Questions

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I am getting this
root(23*a^6*z^3 – 1075392*a^6*z^2 – 720*a^8*z^2 – 793497600*a^4*z^2 + 17471324160*a^6*z + 17031168*a^8*z – 27648*a^10*z + 4019957268480*a^4*z + 248656057860096*a^2*z + 1111306272768*a^8 + 1117403052244992*a^4 + 12586608230400*a^6 + 1353646080*a^10 + 442368*a^12 – 781755859725189120*a^2 + 961852771978444800, z, 1)^(1/2)
when I used the command
Det=collect(det(A),Rh);
Dc=coeffs(Det,Rh,"All");
Dr=roots(Dc);
Rh and a are my variables and I want the value of Rh in a.
I have tried the command simplify also.I am getting this
root(23*a^6*z^3 – 1075392*a^6*z^2 – 720*a^8*z^2 – 793497600*a^4*z^2 + 17471324160*a^6*z + 17031168*a^8*z – 27648*a^10*z + 4019957268480*a^4*z + 248656057860096*a^2*z + 1111306272768*a^8 + 1117403052244992*a^4 + 12586608230400*a^6 + 1353646080*a^10 + 442368*a^12 – 781755859725189120*a^2 + 961852771978444800, z, 1)^(1/2)
when I used the command
Det=collect(det(A),Rh);
Dc=coeffs(Det,Rh,"All");
Dr=roots(Dc);
Rh and a are my variables and I want the value of Rh in a.
I have tried the command simplify also. I am getting this
root(23*a^6*z^3 – 1075392*a^6*z^2 – 720*a^8*z^2 – 793497600*a^4*z^2 + 17471324160*a^6*z + 17031168*a^8*z – 27648*a^10*z + 4019957268480*a^4*z + 248656057860096*a^2*z + 1111306272768*a^8 + 1117403052244992*a^4 + 12586608230400*a^6 + 1353646080*a^10 + 442368*a^12 – 781755859725189120*a^2 + 961852771978444800, z, 1)^(1/2)
when I used the command
Det=collect(det(A),Rh);
Dc=coeffs(Det,Rh,"All");
Dr=roots(Dc);
Rh and a are my variables and I want the value of Rh in a.
I have tried the command simplify also. roots, simplif MATLAB Answers — New Questions

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