控制理论与应用2017，Vol.34Issue(10)：1396-1402,7.DOI:10.7641/CTA.2017.70045
一类非线性切换系统的自适应神经动态面控制
Adaptive neural dynamic surface tracking control for a class of switched nonlinear systems
摘要
Abstract
An adaptive neural dynamic surface tracking control scheme is presented for a class of uncertain switched nonlinear systems in strict-feedback form under arbitrary switching. In this scheme, dynamic surface control (DSC) tech-nology is introduced into backstepping design approach with common Lyapunov function method. The radial basis function neural network is adopted to approximate constructed unknown upper bound function, and with the help of DSC, the deriva-tives of filter output variables instead of traditional intermediate variables are taken as the neural network (NN) inputs. As a result, the dimension of NN inputs is reduced. Simultaneously, Yong's inequality is used to reduce the number of adjustable parameters of the control scheme. Moreover, it is proved that the proposed scheme is able to guarantee that all the signals in the resulting closed-loop system are semi-globally uniformly ultimately bounded, with tracking error converging to a small neighborhood of zero by appropriately choosing design parameters. Simulation studies are carried out to illustrate the effectiveness of the proposed control.关键词
神经网络控制/切换系统/动态面控制/共同Lyapunov法/后推法Key words
neural network control/switching systems/dynamic surface control/common Lyapunov function/back-stepping分类
信息技术与安全科学引用本文复制引用
王加朋,胡跃明,罗家祥..一类非线性切换系统的自适应神经动态面控制[J].控制理论与应用,2017,34(10):1396-1402,7.基金项目
国家自然科学基金项目(61573146),国家科技重大专项(2014ZX02503–3),中央高校业务经费项目资助. Supported by National Natural Science Foundation of China (61573146), National Science and Technology Major Project of China (2014ZX02503–3) and Fundamental Research Funds for the Central Universities of China. （61573146）
