PID controller optimization of mobile robot servo system

Abstract

The device driver control of wheeled mobile robot is based on the PID control of kinetic model. In this paper, to improve the system's overall robustness and the accuracy of control, the wheeled mobile robot's servo drive system is identified by the BP neural network of series-parallel identification structure, and the PID controller parameter is optimized by the genetic algorithm based on the afore identification result. Thereby the global parameter optimization is achieved. Finally, the algorithm is applied in device driver control of the actual robot to prove that the method can effectively improve stableness and accuracy of the speed control, and the optimization problem of the drive servo PID controller of wheeled mobile is solved. And it will provide technical support of the future research of accurate motion in the industrial and agricultural field.