Finite Time Convergent Wavelet Neural Network Sliding Mode Control Guidance Law with Impact Angle Constraint

作     者：Qing-Chun Li Wen-Sheng Zhang Gang Han Ying-Hua Zhang 

作者机构：Institute of Automation Chinese Academy of Sciences 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2015年第12卷第6期

页      面：588-599页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 081105[工学-导航、制导与控制] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China(Nos.U1135005 and 61304224) General Equipment Department Advanced Research Project of China(No.51301010206) 

主　　题：Guidance law sliding mode control wavelet neural n 

摘      要：This paper presents a novel guidance law to intercept non-maneuvering targets with impact angle and lateral acceleration command constraints. Firstly, we formulate the impact angle control to track the desired line-of-sight(LOS) angle, which is achieved by selecting the missile s lateral acceleration to enforce the sliding mode on a sliding surface at impact time. Secondly, we use the Lyapunov stability theory to prove the stability and finite time convergence of the proposed nonlinear sliding surface. Thirdly, we introduce the wavelet neural network(WNN) to adaptively update the additional control command and reduce the high-frequency chattering of sliding mode control(SMC). The proposed guidance law, denoted WNNSMC guidance law with impact angle constraint,combines the SMC methodology with WNN to improve the robustness and reduce the chattering of the system. Finally, numerical simulations are performed to demonstrate the validity and effectiveness of the WNNSMC guidance law.