caa a22 4500 606206094 CHVBK 20210128101010.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00034-015-9971-1 doi (NATIONALLICENCE)springer-10.1007/s00034-015-9971-1 A Neural Network Approach for Tracking Control of Uncertain Switched Nonlinear Systems with Unknown Dead-Zone Input [Elektronische Daten] [Lei Yu, Shumin Fei, Gang Yang] This paper is concerned with adaptive neural tracking control problem for uncertain switched nonlinear systems with unknown dead-zone input. Multilayer neural networks (MNNs) are employed to approximate unknown nonlinear functions, and an adaptive neural network controller is introduced to enhance system robustness. With the proposed control scheme, boundedness of all the signals of the closed-loop system is established regardless of the parameter adjustment mechanism, and better tracking control performance can eventually be achieved in view of the universal approximation capability of MNNs. Also, a switching signal is suitably defined using average dwell-time technique. By using a switching control scheme, it is demonstrated that the transient performance and stability can be simultaneously obtained. Finally, a simulation example is given to illustrate the effectiveness and validity of this approach. Springer Science+Business Media New York, 2015 Adaptive neural tracking control nationallicence Switched nonlinear systems nationallicence Dead-zone input nationallicence Switching signal nationallicence Yu Lei School of Mechanical and Electric Engineering, Soochow University, 215021, Suzhou, China aut Fei Shumin Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, 210096, Nanjing, China aut Yang Gang Digital Manufacture Technology Key Laboratory of JiangSu Province, 223003, Huaian, China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2695-2710 0278-081X 34:8<2695 2015 34 34 https://doi.org/10.1007/s00034-015-9971-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-015-9971-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yu Lei School of Mechanical and Electric Engineering, Soochow University, 215021, Suzhou, China aut NATIONALLICENCE 700 1- Fei Shumin Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, 210096, Nanjing, China aut NATIONALLICENCE 700 1- Yang Gang Digital Manufacture Technology Key Laboratory of JiangSu Province, 223003, Huaian, China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2695-2710 0278-081X 34:8<2695 2015 34 34