Mingyi Gang, Xiao-hai Pan, Kaiyuan Tang, Xingguo Xia, Ben Feng
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Trajectory tracking control strategy of manipulator based on improved particle swarm optimization algorithm
In view of the manipulator system is a highly coupled, nonlinear dynamic characteristics and the system structure and parameters , such as there are many unpredictable factors in the practical work of multiple input multiple output system, designed a fuzzy neural network controller, and combined with particle swarm optimization algorithm for fuzzy neural network controller parameter setting. Through MATLAB simulation, it is proved that the scheme has strong robustness and stability for the control system, and effectively solves the trajectory tracking problem of manipulator.