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Author SHA1 Message Date
EmaMaker d292f7628d misc docs stuff 2024-01-13 13:09:21 +01:00
EmaMaker 23e47d2a14 [ATTEMPT] PID to keep robot still 2024-01-13 13:09:06 +01:00
EmaMaker 2234b5a619 sim: nonlinear simulation
Demonstrates both the analytical solution and the current PID values work
2024-01-13 13:06:52 +01:00
EmaMaker f336e3776f update .gitignore 2024-01-13 13:06:41 +01:00
EmaMaker 0ab95f393e firmware: use pid from new simulation
really big oscillations, somewhat stable
2024-01-12 19:41:34 +01:00
EmaMaker 1266d68b07 sim: let matlab derive transfer function
and recalibrate pid with that
2024-01-12 19:41:06 +01:00
EmaMaker 7b7c09714d [UNSURE] open-loop wheel sync 2024-01-12 13:43:05 +01:00
EmaMaker b5798d2eb3 Revert "pid: eyeballed for a fully charged battery"
This reverts commit 23e63c7625.
2024-01-12 13:34:05 +01:00
EmaMaker 9f02ddf349 update README.md 2024-01-05 15:58:03 +01:00
EmaMaker 23e63c7625 pid: eyeballed for a fully charged battery
Made a video showing the result. Apparently the center of mass is not exactly at the center of the
robot and the battery needs to stick out a bit at the front to rebalance it.

Also my desk is a bit tilted so the pitch is heavily affected by the yaw, the video shows it
clearly. Next step: a inner control loop for the yaw.
2024-01-05 14:39:14 +01:00
40 changed files with 3247 additions and 20 deletions

3
.gitignore vendored
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@ -1,2 +1,5 @@
matlab-sim/slprj/
matlab-sim/*.slxc
matlab-sim-v2/slprj/
matlab-sim-v2/*.slxc
**/*.autosave

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@ -4,15 +4,17 @@ My attempt at building a two-wheeled self-balancing robot. The project started a
later evolved as a University project. I'll upload the university report to this repo as soon as it is complete. This repo will also be
supported by a blog post on [emamaker.com](https://emamaker.com)
The physical model of the robot has been derived by calculatin the Lagrangian function. This model
is heavily non-linear and has been linearized around the 0° point (equilibrium).
The physical model of the robot has been derived by calculating the Lagrangian function. This model
is heavily non-linear and has been linearized around the 0° point of equilibrium.
The linearized model has been reconstructed in MatLab Simulink and a discrete-time PID controller
has been calculated by trial and error.
has been calculated by trial and error. This PID Controller was used to dimension the motors (max. torque
in particular) and was later refined with the Ziegler-Nichols method.
The robot has later been built using a Raspberry Pi Pico microcontroller paired with a MPU6050
6-axis IMU, from which the pitch angle is derived with the use of a [Madgwick](https://ahrs.readthedocs.io/en/latest/filters/madgwick.html) filter.
(Initially this was a simple complementary filter, but it was way to noise, check the blog post).
(Initially this was a simple complementary filter, but it was way too subject to noise from the
accelerometer, check the blog post).
The two motors (Hitec HS-322HD servomotors, check blog post for the choice
of motors) are driven by a L298N motor driver. Everything is powered by a 2S 7.4V LiPo battery.

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@ -6,7 +6,7 @@
constexpr float MOT_SX_MULT = 1.0;
constexpr float MOT_DX_MULT = 1.0;
ArduPID myController;
ArduPID angleCtrl, speedCtrl;
// Calculated with matlab, then adjusted by hand
@ -16,20 +16,31 @@ Pc = 0.083
PID Kp = 0.6Kc, Ti = 0.5Pc Td = 0.125Pc
Ki = KpTc/ti
Kd = KpTd/Tc
*/
*/
constexpr double KP = 6;
constexpr double KI = 0.2;
constexpr double kponkd = 935.9697;
constexpr double kionkd = 1.3189e+04;
constexpr double KD = 0.1;
constexpr double KP = 5.8;
constexpr double KI = 0.2;
//double setpoint = -0.015;
double setpoint = 0.0;
double output = 0;
double input = 0;
double speed_setpoint = 0.0;
double speed_output = 0.0;
double speed_input = 0.0;
double roll{ 0 }, pitch{ 0 }, yaw{ 0 };
constexpr double max_torque_sx = 0.392;
constexpr double max_torque_dx = 0.36;
constexpr double max_torque = max_torque_dx+max_torque_sx;
constexpr double torque_sx_coeff = max_torque_sx/max_torque;
constexpr double torque_dx_coeff = max_torque_dx/max_torque;
void setup(void) {
Serial.begin(9600);
delay(500);
@ -46,11 +57,17 @@ void setup(void) {
update_imu();
}
myController.begin(&input, &output, &setpoint, KP, KI, KD, P_ON_E, FORWARD);
myController.setOutputLimits(-0.72, 0.72); // double of max torque motors can exhert
// myController.setWindUpLimits(-0.2 , 0.02);
myController.setSampleTime(1);
myController.start();
angleCtrl.begin(&input, &output, &setpoint, KP, KI, KD, P_ON_E, FORWARD);
angleCtrl.setOutputLimits(-max_torque, max_torque); // double of max torque motors can exhert
// angleCtrl.setWindUpLimits(-0.2 , 0.02);
angleCtrl.setSampleTime(1);
angleCtrl.start();
speedCtrl.begin(&speed_input, &speed_output, &speed_setpoint, 0, 0.12, 0, P_ON_E, BACKWARD);
speedCtrl.setOutputLimits(-max_torque, max_torque); // double of max torque motors can exhert
speedCtrl.setSampleTime(1);
speedCtrl.start();
digitalWrite(LED_BUILTIN, LOW);
@ -65,18 +82,30 @@ void loop() {
}
void compute(){
static unsigned long last_time;
unsigned long t = millis();
unsigned long dt = millis() - t;
last_time = t;
speedCtrl.compute();
Serial.print(speed_input);
Serial.print(" ");
Serial.println(speed_output);
update_imu();
input = speed_output-pitch;
input = pitch;
angleCtrl.compute();
myController.compute();
double torque = abs(output) * 0.5;
double torque = abs(output);
double s = sign(output);
double pwm_dx = torque <= 0.005 ? 30*s : torque_to_pwm_dx(torque)*s;
double pwm_sx = torque <= 0.005 ? 30*s : torque_to_pwm_sx(torque)*s;
double pwm_dx = torque <= 0.005 ? 30*s : torque_to_pwm_dx(torque*torque_dx_coeff)*s;
double pwm_sx = torque <= 0.005 ? 30*s : torque_to_pwm_sx(torque*torque_sx_coeff)*s;
move_pwm(MOT_SX, pwm_sx);
move_pwm(MOT_DX, pwm_dx);
speed_input = torque*0.5*s;
}

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@ -0,0 +1,6 @@
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% Model of self balancing robot for PID controller
% See scheme anf formulas on notebook
clear all
clc
load('params.mat')
I_wheel = M_wheel*(r^2); %placeholder
I_body = M_body*(l^2)/3; %placeholder
nums1 = -(M_body + 2*(I_wheel/r^2) + 2*M_wheel + M_body*l/r);
nums0 = -2*b/r;
num = [nums1 nums0];
dens3 = I_body * M_body + 2*I_wheel*(I_body*M_body*l^2)/(r^2) + 2*I_body*M_wheel + 2*M_wheel*M_body*l^2;
dens2 = (2*b/r)*(I_body+M_body*g);
dens1 = -( ((M_body^2)*g*l) + 2*(I_wheel*M_body*g*l)/(r^2) + 2*M_body*M_wheel*g*l );
dens0 = -2*(b*M_body*g*l) / r;
den = [dens3 dens2 dens1 dens0];
w = tf(num, den)
sys = zpk(w);
sys.DisplayFormat='roots'
%sys.Z{1}
% sys.P{1}(1)
K = sys.K
p1 = sys.P{1}(1)
p2 = sys.P{1}(3)
p3 = sys.P{1}(2)
%display('Kd must be [' + num2str(p3/K) + ', 0]');
% Scelgo Kd così
kd = -0.001
kponkd = (p1+p2);
kionkd = (p1*p2);
kp = kponkd*kd
ki = kionkd*kd
% rlocus(sys, -sys)
%{
bode(w)
figure;
nyquist(w)
%}

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