Abstract

This paper is concerned with the stability problem for linear discrete-time systems with a time-varying delay. Some relations between two general free-matrix-based summation inequalities are discussed. A novel Lyapunov-Krasovskii functional (LKF) is proposed by modifying the single- and double-summation LKF terms. As a result, a new stability condition is obtained by employing the general free-matrix-based summation inequalities reported recently. Numerical examples are given to show that the obtained stability condition is more relaxed than some of existing results.

Highlights

  • It is well known that time delay, as a natural phenomenon, widely exists in various practical systems such as networked control systems, fuzzy systems and neural networks [1]–[3]

  • The Lyapunov–Krasovskii functional (LKF) method is a powerful tool to deal with the stability problem for linear delayed systems

  • A general free-matrix-based (GFMB) summation inequality is developed [40], which leads to a relaxed stability condition for linear discrete-time systems with a time-varying delay

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Summary

INTRODUCTION

It is well known that time delay, as a natural phenomenon, widely exists in various practical systems such as networked control systems, fuzzy systems and neural networks [1]–[3]. A general free-matrix-based (GFMB) summation inequality is developed [40], which leads to a relaxed stability condition for linear discrete-time systems with a time-varying delay. Chen: New Results on Stability of Linear Discrete-Time Systems With Time-Varying Delay in [26], in which the quadratic augmented vector contains k −1 k −h1 −1 three vectors x(k), x(i) and x(i), where x(k) is i=k −h1 i=k −h2 the state, h1 and h2 are, respectively, the lower and upper bounds of the discrete-time delay. This proposed LKF is later widely used in the few years in the literature. Sn+ represents the set of symmetric positive-definite matrices of Rn×n

PRELIMINARY AND USEFUL LEMMAS
NUMERICAL EXAMPLES
CONCLUSION
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