Disturbance observer for 2DOF robot manipulator
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Hello, I want to design a disturbance observer (DOB) for a 2-degree-of-freedom (2-DOF) robotic manipulator. I'm using MATLAB for simulation and implementation. Could anyone provide guidance or share a detailed example on how to model the 2-DOF robotic manipulator and implement the disturbance observer in MATLAB? Specifically, how to design and implement a DOB for this system and tips on parameter tuning and simulation in MATLAB. Also, can somone tell me if this equations for 2DOF arm are correct:
, where , , ,
From which it follows:
Any help or example code would be greatly appreciated! Thanks.
3 commentaires
Sam Chak
le 10 Juil 2024
What is the Disturbance Observer for?
The compact equations you posted are typical 2nd-order ODEs that can be used to describe the motion of many mechanical systems. But the symbols alone cannot describe the 2-DOF Robotic Manipulator.
If the MATLAB codes are available, would you know how to design the Disturbance Observer?
Keep in mind that the Disturbance Observer alone cannot control the motion of the Robotic Manipulator.
Réponses (1)
Francisco J. Triveno Vargas
le 17 Juil 2024
Déplacé(e) : Sam Chak
le 18 Juil 2024
@HD, inititally you can use this code:
clc
clear
close all
% Time---------------------------------------------------------------------
tf=10;
N=2000*tf;
Nt=tf/N;
t=0:tf/N:tf;
% DoF----------------------------------------------------------------------
n=2;
% Start and end points-----------------------------------------------------
xi=0;
yi=1.73;
xf=1.5;
yf=0;
% Parameters---------------------------------------------------------------
a1=1;
a2=1;
ac1=a1/2;
ac2=a2/2;
m1=2;
m2=2;
mp=0.25;
g0=9.81;
Izz1=1/12*m1*a1^2;
Izz2=1/12*m2*a2^2;
% Inverse kinematics-------------------------------------------------------
xin2=real(acos((xi^2+yi^2-a1^2-a2^2)/(2*a1*a2)));
xin1=real(atan2(yi,xi))-real(atan2(a2*sin(xin2),(a1+a2*cos(xin2))));
xin3=0;
xin4=0;
xdes2=real(acos((xf^2+yf^2-a1^2-a2^2)/(2*a1*a2)));
xdes1=real(atan2(yf,xf))-real(atan2(a2*sin(xdes2),(a1+a2*cos(xdes2))));
xdes3=0;
xdes4=0;
x_0=[xin1;xin2;xin3;xin4];
x_des=[xdes1;xdes2;xdes3;xdes4];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Solution-----------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for i=1:1:length(t)
Time=t(i);
x(:,1)=x_0;
% States---------------------------------------------------------------
q1=x(1,i);
q2=x(2,i);
dq1=x(3,i);
dq2=x(4,i);
q=[q1;q2];
dq=[dq1;dq2];
% Dynamics-------------------------------------------------------------
M=[Izz1+Izz2+a1^2*m2+ac1^2*m1+ac2^2*m2+a1^2*mp+a2^2*mp+2*a1*ac2*m2*cos(q2)+2*a1*a2*mp*cos(q2),mp*a2^2+a1*mp*cos(q2)*a2+m2*ac2^2+a1*m2*cos(q2)*ac2+Izz2;...
mp*a2^2+a1*mp*cos(q2)*a2+m2*ac2^2+a1*m2*cos(q2)*ac2+Izz2,mp*a2^2+m2*ac2^2+Izz2];
g=[g0*m2*(ac2*cos(q1+q2)+a1*cos(q1))+g0*mp*(a2*cos(q1+q2)+a1*cos(q1))+ac1*g0*m1*cos(q1);...
g0*cos(q1+q2)*(ac2*m2+a2*mp)];
C=[-a1*dq2*sin(q2)*(ac2*m2+a2*mp),-a1*sin(q2)*(dq1+dq2)*(ac2*m2+a2*mp);...
a1*dq1*sin(q2)*(ac2*m2+a2*mp),0];
Df=diag([0.1,0.1]);
% Input----------------------------------------------------------------
Kp=5*eye(2);
Kd=10*eye(2);
u(:,i)=-Kp*(q-x_des(1:2))-Kd*(dq-x_des(3:4))+g;
% System---------------------------------------------------------------
f=[dq;inv(M)*(u(:,i)-C*dq-g-Df*dq)];
x(:,i+1)=x(:,i)+f*Nt;
% Error----------------------------------------------------------------
xe2=a1*cos(q1)+a2*cos(q1+q2);
ye2=a1*sin(q1)+a2*sin(q1+q2);
error(i)=sqrt((xe2-xf)^2+(ye2-yf)^2);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Plots--------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
End_Effector_error_m=error(length(t))
figure(1)
hold all;grid on;box on
plot(t,x(1,1:length(t)),'b','LineWidth',1.5)
line([0,tf],[x_des(1),x_des(1)],'LineStyle','--','Color',[1 0 0])
xlabel('t[s]')
ylabel('q_1(t)[rad]')
figure(2)
hold all;grid on;box on
plot(t,x(2,1:length(t)),'b','LineWidth',1.5)
line([0,tf],[x_des(2),x_des(2)],'LineStyle','--','Color',[1 0 0])
xlabel('t[s]')
ylabel('q_2(t)[rad]')
figure(3)
hold all;grid on;box on
plot(t,x(3,1:length(t)),'b','LineWidth',1.5)
line([0,tf],[x_des(3),x_des(3)],'LineStyle','--','Color',[1 0 0])
xlabel('t[s]')
ylabel('dq_1(t)/dt[rad/s]')
figure(4)
hold all;grid on;box on
plot(t,x(4,1:length(t)),'b','LineWidth',1.5)
line([0,tf],[x_des(4),x_des(4)],'LineStyle','--','Color',[1 0 0])
xlabel('t[s]')
ylabel('dq_2(t)/dt[rad/s]')
figure(5)
hold all;grid on;box on
plot(t,u(1,1:length(t)),'b','LineWidth',1.5)
xlabel('t[s]')
ylabel('u_1(t)')
figure(6)
hold all;grid on;box on
plot(t,u(2,1:length(t)),'b','LineWidth',1.5)
xlabel('t[s]')
ylabel('u_2(t)')
q1=x(1,:);
q2=x(2,:);
xe1=a1*cos(q1);
ye1=a1*sin(q1);
xe2=a1*cos(q1)+a2*cos(q1+q2);
ye2=a1*sin(q1)+a2*sin(q1+q2);
figure(7)
hold all
plot(xi,yi,'*r')
plot(xf,yf,'om')
plot(xe2,ye2,'-k','LineWidth',2)
for i=1:round(N/50):N
line([0;xe1(i)],[0;ye1(i)],'Color',[0 0 1])
line([xe1(i);xe2(i)],[ye1(i);ye2(i)],'Color',[1 0 0])
end
xlabel('x(t)[m]')
ylabel('y(t)[m]')
axis equal
box on
grid on
legend('start point','end point','trajectory')
figure(8)
hold all;grid on;box on
plot(t,error(1:length(t)),'b','LineWidth',1.5)
xlabel('t[s]')
ylabel('|error(t)|')
extracted from https://www.mathworks.com/matlabcentral/fileexchange/166431-pd-gravity-control-2dof-planar-robotic-manipulator
For the observer you need to linearize the nonlinear model of manipulador and use it.
Regards
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