Research Papers

Observer-Based Finite-Time Nonfragile Control for Nonlinear Systems With Actuator Saturation

[+] Author and Article Information
R. Sakthivel

Department of Applied Mathematics,
Bharathiar University,
Coimbatore 641046, India
e-mail: krsakthivel0209@gmail.com

R. Mohana Priya

Department of Applied Mathematics,
Bharathiar University,
Coimbatore 641046, India
e-mail: wishesmona@gmail.com

Chao Wang

Department of Mathematics,
Yunnan University,
Kunming 650091, Yunnan, China
e-mail: chaowang@ynu.edu.cn

P. Dhanalakshmi

Department of Applied Mathematics,
Bharathiar University,
Coimbatore 641046, India
e-mail: viga_dhanasekar@yahoo.co.in

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received March 31, 2018; final manuscript received October 30, 2018; published online November 28, 2018. Assoc. Editor: Bernard Brogliato.

J. Comput. Nonlinear Dynam 14(1), 011004 (Nov 28, 2018) (9 pages) Paper No: CND-18-1140; doi: 10.1115/1.4041911 History: Received March 31, 2018; Revised October 30, 2018

This paper considers a design problem of dissipative and observer-based finite-time nonfragile control for a class of uncertain discrete-time system with time-varying delay, nonlinearities, external disturbances, and actuator saturation. In particular, in this work, it is assumed that the nonlinearities satisfy Lipschitz condition for obtaining the required results. By choosing a suitable Lyapunov–Krasovskii functional, a new set of sufficient conditions is obtained in terms of linear matrix inequalities, which ensures the finite-time boundedness and dissipativeness of the resulting closed-loop system. Meanwhile, the solvability condition for the observer-based finite-time nonfragile control is also established, in which the control gain can be computed by solving a set of matrix inequalities. Finally, a numerical example based on the electric-hydraulic system is provided to illustrate the applicability of the developed control design technique.

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Grahic Jump Location
Fig. 1

States of x1(k) and its estimate

Grahic Jump Location
Fig. 2

States of x2(k) and its estimate

Grahic Jump Location
Fig. 5

Time history of x̃T(k)Rx̃(k)

Grahic Jump Location
Fig. 6

Estimation of domain of attraction



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