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%% Least Squares with Linear Constraints and Bounds % Find the |x| that minimizes the norm of |C*x - d| for an overdetermined % problem with linear inequality constraints and bounds. %% % Specify the problem and constraints. C = [0.9501 0.7620 0.6153 0.4057 0.2311 0.4564 0.7919 0.9354 0.6068 0.0185 0.9218 0.9169 0.4859 0.8214 0.7382 0.4102 0.8912 0.4447 0.1762 0.8936]; d = [0.0578 0.3528 0.8131 0.0098 0.1388]; A = [0.2027 0.2721 0.7467 0.4659 0.1987 0.1988 0.4450 0.4186 0.6037 0.0152 0.9318 0.8462]; b = [0.5251 0.2026 0.6721]; Aeq = [3 5 7 9]; beq = 4; lb = -0.1*ones(4,1); ub = 2*ones(4,1); %% % Call |lsqlin| to solve the problem. options = optimoptions('lsqlin','Algorithm','interior-point'); x = lsqlin(C,d,A,b,Aeq,beq,lb,ub,[],options)