Decentralized Adaptive Fuzzy Sliding Mode Observer Design for Large-Scale Systems with Unknown Interconnections in the presence of Lumped Perturbation

Abstract

In this manuscript, a class of large-scale systems with lumped perturbations and unknown interconnections between subsystems is studied. A decentralized adaptive fuzzy sliding mode observer is proposed to estimate states using the output of each subsystem. In the large-scale systems under study, it is assumed that only limited information is available on the subsystem interconnections and the interconnection matrix is unknown. The combination of the Luenberger and sliding mode technique is used to estimate non-measured states and to observe the effects of unknown interconnections between subsystems, An adaptive approach is proposed that the matrix of interconnection between subsystems is estimated. Also, the sliding term is designed by fuzzy rules so that the error of convergence between the real state and the estimated state is zero and reduce chattering. Finally, by selecting a Lyapunov function and appropriate design parameters, the convergence of the estimation error to zero is guaranteed. To illustrate the performance of the proposed decentralized adaptive fuzzy sliding mode, a numerical example with a series of simulations is presented.

Keywords

• decentralized observer
• fuzzy theory
• sliding mode observer
• large scale system
• adaptive law
• lyapunov function