Identification and Control of Hyperchaotic Lorenz System Based on Quantum Inspired PSO and Wavelet Neural Network  

作　　者：Kun Zhang Wei Zheng 

机构地区：[1]School of Mathematics and Statistics,Chuxiong normal university,Chuxiong Yunnan 675000,China

出　　处：《控制工程期刊（中英文版）》2019年第1期1-12,共12页Scientific Journal of Control Engineering

基　　金：National Natural Science Foundation of China(No.11261001)。

摘　　要：For the identification and control problem of hyperchaotic Lorenz system,a method of feedback compensation control based on quantum inspired PSO and wavelet neural network(PSOQI-Wavelet Neural Network)is proposed.Firstly,the quantum principle obtained from Quantum PSO(QPSO)has been combined with standard PSO to form a new hybrid algorithm called PSO with Quantum Infusion(PSO-QI).Then,the parameters of wavelet neural network were optimized with PSO-QI and feedback compensation control for hyperchaotic Lorenz system is implemented using optimized PSOQI-Wavelet Neural Network.The numerical simulation results showed that this method has better precision and can quickly track given hyperchaotic Lorenz system.

关 键 词：Hyperchaotic Lorenz System Chaotic Control Quantum Inspired PSO Wavelet Neural Network 

分 类 号：O41[理学—理论物理]