Multiobjective optimization of autonomous control for a biped robot
In the present study, a multiobjective particle swarm optimization (PSO) is used to Pareto optimal design of controller for a biped robot walks in the coronal plane. Both nonlinearity of the dynamic equations and the tracking system cause an effective control that has to be used to address these problems.Thus, the proportional-derivative control is employed to control of the robot in the coronal plane, and the multiobjective algorithm is utilized to tune the heuristic parameters of the controller. The obtained Pareto front by the multiobjective PSO algorithm is compared with three prominent algorithms: modified NSGAII, sigma method, and MATLAB® Toolbox MOGA.
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