Digital sliding mode controller design for multiple time-delay continuous-time transfer function matrices with a long input–output delay. (January 2015)

• Record Type: Journal Article
• Authors: Xie, L.B.; Shieh, L.S.; Wu, C.Y.; Tsai, J.S.H.; Canelon, J.I.; Singla, M.
• Is Part Of: Journal of process control. Volume 25(2015:Jan.)
• Page Start: 78
• Page End: 93
• Publication Date: 2015-01
• Subjects: Multiple time delays -- Sliding mode controller -- Optimal control -- Digital redesign; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2014.11.003
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: A reduced-order discrete/continuous-time model with input/output delays for multiple time-delayed processes is proposed. The delay-free optimal sliding mode controller design methodology is extended to multiple time-delayed processes. The prediction-based digital redesign method is newly developed for multiple time-delayed transfer function matrices. Low-dimensional digital sliding mode controller and observer for multiple time-delayed processes are proposed. Abstract: This paper extends the dominant eigenvector-based sliding mode control (SMC) design methodology, which was originally developed for delay-free continuous-time processes with known parameters, to the case of multiple time-delay continuous-time processes with known/unknown parameters. In addition, this paper presents a new prediction-based Chebyshev quadrature digital redesign methodology for indirect design of the digital counterpart of the analog sliding mode controller (ASMC) for multiple time-delay continuous-time transfer function matrices with either a long input delay or a long output delay. An approximated discrete-time model and its corresponding continuous-time model are constructed for multiple time-delay continuous-time stable/unstable dynamical processes with known/unknown parameters, using first the conventional observer/Kalman filter identification (OKID) method. Then, an optimal ASMC is developed using the linear quadratic regulator (LQR) approach, in which the corresponding sliding surface is designed using the user-specified eigenvectors and the scalar sign function. For digital implementation of the proposed non-augmented low-dimensional ASMC, a digital counterpart is designed based on the existing prediction-based digital redesign method and the newly developed prediction-based Chebyshev quadrature digital redesign method. Finally, a non-augmented low dimensional digital observer with a long input or output dead time is constructed for the implementation of the digitally redesigned sliding mode controller, to improve the performances of multiple time-delay dynamical processes. The effectiveness of the proposed method has been verified by means of two illustrative examples.