Robust Control of Robot Dexterity Operation Based on Harmony Search Genetic Algorithm

Abstract

In response to the characteristics of multiple variables, uncertain parameters, complex structure, and strong coupling in the agile operation control system of robots, an adaptive genetic algorithm with cross probability and mutation probability is adopted to improve the control rate and steady-state accuracy of the control system. Integrating harmony search algorithm thinking with genetic algorithm to further optimize the parameters of the robot's agile operation controller in the initial population generation process. The simulation has verified that the optimization algorithm can effectively improve the control efficiency, steady-state accuracy, and robustness of the controller, and can ensure that the overshoot value of the system is within an appropriate range.