76 lines
3.2 KiB
Matlab
76 lines
3.2 KiB
Matlab
% load pendubot data
|
|
% rawData = load('current_A_0.7_v_1.mat');
|
|
rawData = load('current_A_5_v_4.mat');
|
|
|
|
% parse pendubot data
|
|
pendubot.time = rawData.data(:,1) - rawData.data(1,1);
|
|
pendubot.current = rawData.data(:,2);
|
|
pendubot.current_desired = rawData.data(:,4);
|
|
pendubot.torque = rawData.data(:,3);
|
|
|
|
pendubot.shldr_position = rawData.data(:,7) - pi/2; % to fit model
|
|
pendubot.shldr_velocity = rawData.data(:,9);
|
|
pendubot.elbw_position = rawData.data(:,8);
|
|
pendubot.elbw_velocity = rawData.data(:,10);
|
|
|
|
pendubot.position_desired = rawData.data(:,5);
|
|
pendubot.velocity_desired = rawData.data(:,6);
|
|
|
|
% filter velocties with zero phas filter
|
|
vlcty_fltr = designfilt('lowpassiir','FilterOrder',5, ...
|
|
'HalfPowerFrequency',0.25,'DesignMethod','butter');
|
|
pendubot.shldr_velocity_filtered = filtfilt(vlcty_fltr, pendubot.shldr_velocity);
|
|
pendubot.elbw_velocity_filtered = filtfilt(vlcty_fltr, pendubot.elbw_velocity);
|
|
|
|
% estimating accelerations based on filtered velocities
|
|
q2d1 = zeros(size(pendubot.shldr_velocity));
|
|
q2d2 = zeros(size(pendubot.elbw_velocity));
|
|
for i = 2:size(pendubot.shldr_velocity,1)-1
|
|
q2d1(i) = (pendubot.shldr_velocity_filtered(i+1) - pendubot.shldr_velocity_filtered(i-1))/...
|
|
(pendubot.time(i+1) - pendubot.time(i-1));
|
|
q2d2(i) = (pendubot.elbw_velocity_filtered(i+1) - pendubot.elbw_velocity_filtered(i-1))/...
|
|
(pendubot.time(i+1) - pendubot.time(i-1));
|
|
end
|
|
pendubot.shldr_acceleration = q2d1;
|
|
pendubot.elbow_acceleration = q2d2;
|
|
|
|
% filter estimated accelerations with zero phase filter
|
|
aclrtn_fltr = designfilt('lowpassiir','FilterOrder',5, ...
|
|
'HalfPowerFrequency',0.25,'DesignMethod','butter');
|
|
pendubot.shldr_acceleration_filtered = filtfilt(aclrtn_fltr, pendubot.shldr_acceleration);
|
|
pendubot.elbow_acceleration_filtered = filtfilt(aclrtn_fltr, pendubot.elbow_acceleration);
|
|
|
|
% filter torque measurements using zero phase filter
|
|
trq_fltr = designfilt('lowpassiir','FilterOrder',5, ...
|
|
'HalfPowerFrequency',0.2,'DesignMethod','butter');
|
|
pendubot.torque_filtered = filtfilt(trq_fltr, pendubot.torque);
|
|
|
|
|
|
% Validation
|
|
vldtnRange = 1:200;
|
|
tau_prdctd_OLS = []; tau_prdctd_SDP = [];
|
|
for i = vldtnRange
|
|
qi = [pendubot.shldr_position(i), pendubot.elbw_position(i)]';
|
|
qdi = [pendubot.shldr_velocity_filtered(i), pendubot.elbw_velocity_filtered(i)]';
|
|
q2di = [pendubot.shldr_acceleration_filtered(i), pendubot.elbow_acceleration_filtered(i)]';
|
|
|
|
if plnrBaseQR.motorDynamicsIncluded
|
|
Yi = regressorWithMotorDynamicsPndbt(qi, qdi, q2di);
|
|
else
|
|
Yi = full_regressor_plnr(qi, qdi, q2di);
|
|
end
|
|
Ybi = Yi*plnrBaseQR.permutationMatrix(:,1:plnrBaseQR.numberOfBaseParameters);
|
|
Yfrctni = frictionRegressor(qdi);
|
|
tau_prdctd_OLS = horzcat(tau_prdctd_OLS, [Ybi, Yfrctni]*pi_hat);
|
|
tau_prdctd_SDP = horzcat(tau_prdctd_SDP, [Ybi, Yfrctni]*[pi_b; pi_frctn]);
|
|
end
|
|
|
|
%%
|
|
figure
|
|
plot(pendubot.time(vldtnRange), pendubot.torque(vldtnRange),'r')
|
|
hold on
|
|
plot(pendubot.time(vldtnRange), tau_prdctd_OLS(1,:),'b-')
|
|
plot(pendubot.time(vldtnRange), tau_prdctd_SDP(1,:),'k-')
|
|
% plot(pendubot.time(vldtnRange), pendubot.torque(vldtnRange) - tau_prdctd(1,:)', 'k--')
|
|
legend('measured', 'predicted OLS', 'predicted SDP')
|
|
grid on |