Abstract
The problem of the guaranteed cost control for uncertain genetic regulatory networks with interval time-varying delays is investigated in this paper, that is, to design a state feedback controller such that the resultant closed-loop system is robustly asymptotically stable and its linear quadratic performance has an upper bound. Lyapunov function and convex combination approaches are employed to establish a sufficient condition for the existence of expected controllers, and a cone complementarity linearization technique is used to transform the controller design problem into a sequential minimization one with linear matrix inequality constraints, which can be solved efficiently by using existing optimization techniques. Finally, a numerical example is provided to show the effectiveness of the proposed method.
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