Intelligent control for Hammerstein nonlinear systems with arbitrary deadzone input. (April 2017)

• Record Type: Journal Article
• Authors: Zhang, Bi; Mao, Zhizhong; Zhang, Tingfeng
• Other Names: Wu Zhipeng guest-editor.
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 39:Number 4(2017)
• Page Start: 567
• Page End: 578
• Publication Date: 2017-04
• Subjects: Intelligent control -- Hammerstein models -- arbitrary deadzone -- adaptive control -- multiple models -- neural networks -- stability; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331215611934
• Languages: English
• ISSNs: 0142-3312

Abstract

In this paper, a new intelligent control scheme based on multiple models and neural networks is proposed to adaptively control a class of Hammerstein nonlinear systems with arbitrary deadzone input. This approach consists of a linear robust adaptive controller, multiple neural networks-based nonlinear adaptive controllers and a switching mechanism. Since the control input is derived from a modified certainty equivalent principle, the manner in which the closed-loop stability is established forms the main contribution. To show the usefulness of the developed results, three simulation examples, including a direct current motor subject to a nonlinear friction, are studied.