Chaos Control for A Class of Vibro-Impact System Based on PSO Optimization

In view of the chaos control problem for a single-degree-of-freedom vibro-impact system with clearance, a parameter feedback control method of chaotic motion based on radial basis function neural network (RBFNN) optimized by particle swarm optimization(PSO) was proposed. Firstly, the correlation relationship and its performance characteristics between chaotic motion and excitation frequency change were analyzed, and the parameter analysis criteria of bifurcation and chaotic motion were summarized. Then, a parameter feedback chaotic controller of radial basis function (RBF) neural network was designed on the basis of the analysis. Secondly, a fitness function aiming at minimizing the distance between two adjacent points on the Poincaré section was constructed to guide the PSO algorithm to optimize the parameters of the controller. Finally, a small perturbation was applied to the controllable parameters of the system to control the chaotic motion as a stable periodic motion. This method can be applied to chaotic motion control where the model is unknown or the precise mathematical model is difficult to establish. The feasibility and effectiveness of the proposed control method were verified by simulation results.