Metaheuristics-based Multi-objective Design of Global Robust Optimal Sliding Mode Control of Discrete Uncertain Systems

This article proposes a novel robust adaptive sliding control mode law for time unknown varying delay in state uncertain systems. In this work, the upper limit of disruption and uncertainty is assumed to be unknown. The model is adjusted so that the system looks like a certain one with unknown added disturbances on the bounds of which are unknown too. Accordingly, new control law for this kind of systems has been defined based on a Lypunov function choice. The main results of this paper are that the conditions for the existence of linear sliding surfaces are derived within the linear matrix inequalities (LMIs) framework by employing the free weighting matrices and the determination of the control law based on a sliding surface will converge to zero. This proposed approach has been validated in simulation on an uncertain system with comparative study proved the efficiency of the proposed resulting methodology after has been validated in real system.

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Metaheuristics-based Multi-objective Design of Global Robust Optimal Sliding Mode Control of Discrete Uncertain Systems

Cited by 2 publications

References 28 publications

Characteristic Model-based Adaptive Control with Genetic Algorithm Estimators for Four-PMSM Synchronization System

Characteristic Model-based Adaptive Control with Genetic Algorithm Estimators for Four-PMSM Synchronization System

A New Robust Adaptive Sliding Mode Control for Discrete-Time Systems With Time-Varying State Delay

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