Optimization of PID parameter tuning for gravity stabilized platform based on improved differential evolutionary algorithm

Abstract

Abstract To address the difficulty of the PID controller parameters tuning of gravity stabilized platform, an improved differential evolutionary (IDE) algorithm containing two currently better variational strategies is proposed. In the process of algorithm iteration, the mutation factor and crossover probability factor of the algorithm are gradually changed to improve the optimization performance of the algorithm. On this basis, the improved differential evolution algorithm is applied to the PID controller parameter tuning problem of gravity stabilized platform. Simulation results show that the algorithm is effective and can be used to optimize the parameters of PID controller of gravity stabilization platform.