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Ching-Chih Tsai,Hsiao-Lang Wu 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Passivity and its applications to mechatronic systems have been widely investigated and continuously improved for many years. This paper presents methodologies for adaptive global stabilization and disturbance attenuation of a class of weekly minimum-phase nonlinear uncertain systems, which can be either of nonlinear affine or of relative degree 1. Adaptive passivity-based control (PBC) methods are developed to achieve adaptive stabilization and disturbance attenuation for the systems with some unknown but constant parameters. Sufficient conditions and state regulations are established for showing the closed-loop system to be globally stable. The merit and performance of the proposed methods are exemplified by conducting several simulations on a 2-linked manipulator. The developed techniques may be of interest to professionals working in the field of nonlinear passive control and its applications.
Indirect Adaptive Nonlinear Self-Balancing and Station Keeping for Omnidirectional Riding Chair
Ching-Chih Tsai,Yi-Ping Ciou,Feng-Chun Tai,Hsiao-Lang Wu 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
This paper presents indirect adaptive self-balancing and station keeping control methods using recurrent Wavelet Fuzzy CMAC (RWFCMAC) for an omnidirectional ball-driven chair in presence of significant system uncertainties. By backstepping, sliding-mode control and RWFCMAC, the self-balancing controller is synthesized to follow the rider’s inclination angles in both two axes (x-z and y-z axis), and the station-keeping controller is designed to allow the rider to maintain the vehicle at the same place. The RWFCMAC is designed to online learning the uncertainties caused by riders’ weights and different unknown frictions between the ball and terrain surfaces. The superior performance and merit of the proposed control methods are well exemplified by comparing to two existing controllers.