Title :
Neural network adaptive sliding mode control to seesaw systems
Author :
Fan Zhiyong ; Zhang Jinggang
Author_Institution :
Coll. of Electron. Inf. Eng., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
In this paper, a neural network adaptive sliding-mode controller (NNASMC) is proposed for higher-order, nonlinear seesaw systems. At first, the mathematical model of the seesaw system is created. Then, the neural network sliding mode controller is designed to be the main controller, which is used to approach the equivalent control part of sliding mode control. An adaptive sliding mode controller is the compensation controller of the system, and the interference and uncertainties of the system are compensated by it. Finally, sliding mode control based on index reaching law and NNASMC are used to do simulation on a seesaw system respectively. Computer simulation results show that the NNASMC converges very fast and the maximum deviation of the system is very small.
Keywords :
adaptive control; compensation; mathematical analysis; neurocontrollers; nonlinear control systems; variable structure systems; compensation controller; higher-order nonlinear seesaw system; index reaching law; mathematical model; neural network adaptive sliding mode control; system interference; system uncertainty; Adaptive systems; Artificial neural networks; Equations; Mathematical model; Neurons; Sliding mode control; Adaptive; Chattering; Neural Network; Seesaw; Sliding-mode;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6