A direct MRAC based multivariable multiple-model switching control scheme. (October 2017)

• Record Type: Journal Article
• Authors: Tan, Chang; Tao, Gang; Qi, Ruiyun; Yang, Hui
• Is Part Of: Automatica. Volume 84(2017)
• Page Start: 190
• Page End: 198
• Publication Date: 2017-10
• Subjects: Direct adaptive control -- Multiple-model design -- Multivariable adaptive control -- Parameter estimation -- Stability and tracking; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2017.07.020
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: In this paper a direct model reference adaptive control (MRAC) based multiple-model switching control scheme is developed for linear multivariable plants. Such a scheme is capable of ensuring desired system performance, avoiding control singularity and possible persistent control switching. A plant signal identity is used to derive a bank of parameter estimators which are initialized from different parameter subregions. A bank of adaptive controllers are constructed, whose parameters are directly updated from the estimators with globally stable adaptive laws for desired parameter adaptation without control gain matrix inversion to avoid control singularity. A control switching mechanism is designed with performance indexes formed from estimation errors which are directly used in the controller parameter update laws and are closely related to the tracking error, together with the use of a lower threshold switching parameter to ensure the eventual settle-down of the control switching. Closed-loop stability and output tracking are analyzed, and some extensions of the multiple-model design are given. Simulation results are presented to show the desired system performance, especially, improved system transient responses.