NEW RESULTS ON FINITE-TIME GUARANTEED COST CONTROL OF UNCERTAIN NONLINEAR FRACTIONAL-ORDER NEURAL NETWORKS WITH TIME-VARYING DELAY
Abstract
In this paper, we study the problem of guarantees cost control with finite-time for a class of uncertain fractional-order nonlinear neural netwoks with time-varying delay. A quadratic cost function is considered as a performance measure for the closed-loop system. By using linear matrix inequalities (LMIs) and the Laplace transform, several new sufficient conditions are proposed for designing a state feedback controller to ensure that the closed-loop system is finite-time stable and meets the desired performance cost level
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