NDLI: An adaptive terminal iterative learning control for nonaffine nonlinear discrete-time systems

Content Provider	IEEE Xplore Digital Library
Author	Chiang-Ju Chien Ying-Chung Wang Ronghu Chi Dong Shen
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. Eng., Huafan Univ., Taipei, Taiwan (Chiang-Ju Chien; Ying-Chung Wang) \|\| Coll. of Autom. & Electr. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China (Ronghu Chi) \|\| Coll. of Inf. Sci. & Technol., Beijing Univ. of Chem. Technol., Beijing, China (Dong Shen)
Abstract	A new adaptive terminal iterative learning controller is presented in this paper for nonaffine nonlinear discrete-time systems with iteration-varying desired terminal output and random initial system output. A terminal output tracking error model is firstly derived by using the system function and the differential mean value theorem since it is assumed only system terminal output is measurable. Based on the derived terminal output tracking error model, an iteration-varying boundary layer and a dead-zone like auxiliary terminal error are proposed to design an adaptive terminal iterative learning controller. The iterative learning controller and the width of boundary layer are updated from trial to trial in order to compensate for an unknown nominal desired terminal input and an unknown uncertain desire terminal input respectively. Based on a Lyapunov like analysis, we show that the boundedness of control input, system output and width of boundary layer are guaranteed for each iteration and each time instant. Furthermore, the norm of terminal output error will asymptotically converge to a tunable residual set whose size depends on the width of boundary layer as iteration number goes to infinity.
Starting Page	1090
Ending Page	1094
File Size	144881
Page Count	5
File Format	PDF
e-ISBN	9781479970179
DOI	10.1109/CCDC.2015.7162079
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Discrete-time systems Adaptation models Adaptive systems Iteration-Varying Target Nonaffine Nonlinear Systems Force Adaptive Control Terminal Iterative Learning Control Control systems Nonlinear systems
Content Type	Text
Resource Type	Article

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