add estimate
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@ -3,7 +3,7 @@ function out1 = base_regressor_Two_bar(in1,in2,in3)
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% OUT1 = base_regressor_Two_bar(IN1,IN2,IN3)
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% OUT1 = base_regressor_Two_bar(IN1,IN2,IN3)
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% This function was generated by the Symbolic Math Toolbox version 9.1.
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% This function was generated by the Symbolic Math Toolbox version 9.1.
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% 14-Jan-2024 21:45:43
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% 16-Feb-2024 11:59:18
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q2 = in1(2,:);
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q2 = in1(2,:);
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qd1 = in2(1,:);
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qd1 = in2(1,:);
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@ -21,4 +21,6 @@ t9 = t4.^2;
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t10 = t2.*t6;
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t10 = t2.*t6;
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t11 = t3.*t6;
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t11 = t3.*t6;
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t12 = -t8;
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t12 = -t8;
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out1 = reshape([t7+t11+t2.*t5-t3.*t9,t7+t11,t10+t12-t3.*t5-t2.*t9,t10+t12,t5,t5,qdd1,0.0],[2,4]);
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t13 = t7+t11;
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t14 = t10+t12;
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out1 = reshape([t14-t3.*t5-t2.*t9,t14,t13+t2.*t5-t3.*t9,t13,t5,t5,t2.*t13+t3.*(t8-t10),0.0],[2,4]);
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@ -3,7 +3,7 @@ function out1 = standard_regressor_Two_bar(in1,in2,in3)
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% OUT1 = standard_regressor_Two_bar(IN1,IN2,IN3)
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% OUT1 = standard_regressor_Two_bar(IN1,IN2,IN3)
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% This function was generated by the Symbolic Math Toolbox version 9.1.
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% This function was generated by the Symbolic Math Toolbox version 9.1.
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% 14-Jan-2024 21:45:42
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% 16-Feb-2024 11:59:17
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q2 = in1(2,:);
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q2 = in1(2,:);
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qd1 = in2(1,:);
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qd1 = in2(1,:);
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@ -12,6 +12,7 @@ qd=[qd_J; -qd_J];
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qdd=[qdd_J; -qdd_J];
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qdd=[qdd_J; -qdd_J];
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g = [0; 0; -9.8];
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g = [0; 0; -9.8];
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tau = zeros([2,101]);
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tau = zeros([2,101]);
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% pi -> [m;mc;I] 10 element
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robot_pi1=[1;1/2;0;0;1+1/4;0;0;1+1/4;0;1+1/4];
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robot_pi1=[1;1/2;0;0;1+1/4;0;0;1+1/4;0;1+1/4];
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robot_pi2=[2;1;0;0;1+1/4;0;0;1+1/4;0;1+1/4];
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robot_pi2=[2;1;0;0;1+1/4;0;0;1+1/4;0;1+1/4];
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robot_pi=[robot_pi1;robot_pi2];
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robot_pi=[robot_pi1;robot_pi2];
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@ -76,4 +77,10 @@ robot.sol = sol;
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pib_OLS=pinv(Wb)*Tau;
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pib_OLS=pinv(Wb)*Tau;
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pifrctn_OLS = 0;
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pifrctn_OLS = 0;
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end
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end
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function [pib_OLS, pifrctn_OLS] = MultiLeastSquareEstimation(idntfcnTrjctry, Tau, Wb)
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% Function perfroms Multi step ordinary least squares estimation of parameters
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pib_OLS=pinv(Wb)*Tau;
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pifrctn_OLS = 0;
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end
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end
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end
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