Nonlinear inversion-based control with adaptive neural network compensation for uncertain MIMO systems

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• 作者：Jinzhu Peng ; Rickey Dubay ; ^{dubayr@unb.ca}
• 关键词：Neural network ; Nonlinear inversion-based control ; Variable structure control ; H&infin ; control ; Nonlinear MIMO systems
• 刊名：Expert Systems with Applications
• 出版年：2012
• 期刊代码：62_09574174
• 类别：et
• 出版时间：July, 2012
• 卷：39
• 期：9
• 页码：8162-8171
• 文件大小：686 K

摘要

A robust output feedback control scheme for uncertain nonlinear multiple-input and multiple-output (MIMO) systems is proposed, which combines a nonlinear inversion-based controller with a neural network-based robust compensator. The nonlinear inversion-based controller acts as the main controller, and a neural network with an adaptive update law is designed to model the unknown system dynamics, a variable structure controller is employed to eliminate the effect of the neural network approximation errors and to ensure the system stability. Furthermore, an H_{鈭?/sub> controller which is a component of the robust compensator is designed to achieve a certain robust tracking performance and to attenuate the effect of external disturbances to a prescribed level. The proposed approach indicates that the nonlinear inversion-based control method is also valid for controlling uncertain nonlinear MIMO systems with uncertainties and disturbances, provided that a compensative controller is designed appropriately. Simulation results demonstrated that the proposed controller performed better in comparison to the nonlinear inversion-based control method and an advanced neural network-based hybrid controller.}