NDLI: Smooth switching control for discrete-time multi-variable systems with unknown time-varying parameters

Content Provider	IET Digital Library
Author	Hu, Qiong Ma, Hongbin Fei, Qing Geng, Qingbo Wu, Qinghe
Abstract	For a class of discrete-time multi-variable systems with time-varying parametric uncertainty, the parameter identification method and switching control architecture are developed in this study to implement smooth switching control. Specifically, the identification algorithm based on the least geometric mean squares is derived for the multi-variable system. In addition, the switching control system, with model reference control technique as the basis of control design for each local model, is proposed to achieve satisfactory control performance, especially to eliminate the oscillations at the switching boundaries which can be attributed to the difference in the input–output dynamics between the pre- and post-switching closed-loop subsystems. Furthermore, the switching strategy based on neural network classifier is put forward for the accurate switching among a set of model reference controllers which are correspondingly designed for the identified subsystems. Finally, the feasibility and effectiveness of the proposed identification and control schemes are verified by numerical simulations, which show that the desirable identification and control performances are guaranteed under the proposed schemes. Moreover, the advantage of the presented switching control system in terms of smooth switching is validated through comparison with other kinds of control schemes.
Starting Page	944
Ending Page	962
Page Count	19
ISSN	17518644
Volume Number	9
e-ISSN	17518652
Issue Number	Issue 6, Apr (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/9/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2014.0539
Journal	IET Control Theory & Applications
Publisher Date	2015-03-31
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Closed Loop System Discrete Control System Discrete Time System Discrete-time Multivariable System Input-output Dynamics Least Geometric Mean Squares Model Reference Adaptive Control System Model Reference Control Technique Modelling And Identification Multivariable Control System Multivariable System Neural Nets Neural Network Classifier Oscillation Elimination Parameter Estimation Parameter Identification Method Pattern Classification Post Switching Closed-loop SubSystem Preswitching Closed-loop SubSystem Self Adjusting Control System Simulation Smooth Switching Control Switching System (control) Time Varying Control System Time-varying Parametric Uncertainty Uncertain System
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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