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Neural-network adaptive controller for nonlinear systems and its application in pneumatic servo systems
Authors:Lu Lu  Fagui Liu  Weixiang Shi
Institution:1. Department of Computer Science and Engineering, South China University of Technology, Guangzhou Guangdong 510640, China
2. Department of Mechaelectronics Engineering, Xi'an Jiaotong University, Xi'an Shaanxi 710049, China
Abstract:In this paper, a novel control law is presented, which uses neural-network techniques to approximate the affine class nonlinear system having unknown or uncertain dynamics and noise disturbances. It adopts an adaptive control law to adjust the network parameters online and adds another control component according to H-infinity control theory to attenuate the disturbance. This control law is applied to the position tracking control of pneumatic servo systems. Simulation and experimental results show that the tracking precision and convergence speed is obviously superior to the results by using the basic BP-network controller and self-tuning adaptive controller.
Keywords:Nonlinear control  Convergence  Adaptive control  H-infinity control  Neural networks  Pneumatic servo system
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