Neural network control of a class of nonlinear systems with actuator saturation

作者: W. Gao , R.R. Selmic

DOI: 10.1109/TNN.2005.863416

关键词:

摘要: A neural net (NN)-based actuator saturation compensation scheme for the nonlinear systems in Brunovsky canonical form is presented. The that leads to stability, command following, and disturbance rejection rigorously proved verified using a general "pendulum type" robot manipulator dynamical systems. Online weights tuning law, overall closed-loop system performance, boundedness of NN are derived guaranteed based on Lyapunov approach. assumed be unknown compensator inserted into feedforward path. Simulation results indicate proposed can effectively compensate nonlinearity presence uncertainty.

参考文章(32)
A. M. Annaswamy, S. Evesque, S.-I. Niculescu, A. P. Dowling, Adaptive Control of a Class of Time-delay Systems in the Presence of Saturation Springer London. pp. 289- 310 ,(2001) , 10.1007/978-1-4471-3687-3_11
Rastko Selmic, Frank L. Lewis, Javier Campos, Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities ,(1987)
Kumpati S. Narendra, Adaptive control using neural networks Neural networks for control. pp. 115- 142 ,(1990)
F W Lewis, S. Jagannathan, A Yesildirak, Neural Network Control of Robot Manipulators and Nonlinear Systems CRC Press. ,(1998) , 10.1201/9781003062714
C. T. Abdallah, D. M. Dawson, Frank L. Lewis, Control of Robot Manipulators ,(1993)
Ken-Ichi Funahashi, On the approximate realization of continuous mappings by neural networks Neural Networks. ,vol. 2, pp. 183- 192 ,(1989) , 10.1016/0893-6080(89)90003-8
Sheng Lin, A.A. Goldenberg, Neural-network control of mobile manipulators IEEE Transactions on Neural Networks. ,vol. 12, pp. 1121- 1133 ,(2001) , 10.1109/72.950141
B. Igelnik, Yoh-Han Pao, Stochastic choice of basis functions in adaptive function approximation and the functional-link net IEEE Transactions on Neural Networks. ,vol. 6, pp. 1320- 1329 ,(1995) , 10.1109/72.471375
Rastko R. Selmic, Frank L. Lewis, BACKLASH COMPENSATION IN NONLINEAR SYSTEMS USING DYNAMIC INVERSION BY NEURAL NETWORKS Asian Journal of Control. ,vol. 2, pp. 76- 87 ,(2008) , 10.1111/J.1934-6093.2000.TB00147.X
M. Corless, G. Leitmann, Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems IEEE Transactions on Automatic Control. ,vol. 26, pp. 1139- 1144 ,(1981) , 10.1109/TAC.1981.1102785