IEEE Transactions on Fuzzy Systems
Decentralized H∞ filter design for discrete-time interconnected fuzzy systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Decentralized fuzzy H∞filtering for nonlinear interconnected systems with multiple time delays
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Sequential stability analysis and observer design for distributed TS fuzzy systems
Fuzzy Sets and Systems
Adaptive dynamic CMAC neural control of nonlinear chaotic systems with L2 tracking performance
Engineering Applications of Artificial Intelligence
Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems
Applied Soft Computing
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In general, due to the interactions among subsystems, it is difficult to design an H infin-decentralized output-feedback controller for nonlinear interconnected systems. This study introduces H infin-decentralized fuzzy-observer-based fuzzy control design, where the premise variables depend on the state variables estimated by a fuzzy observer, for nonlinear interconnected systems via T-S fuzzy models. The fuzzy control design for this case is more flexible but much more complex than that for the case where the premise variables depend on the state variables only. A novel decoupled method is proposed in this study to transform the non-linear matrix inequality (non-LMI) conditions into some LMI forms. By the proposed decoupled method, the problem of H infin-decentralized fuzzy-observer-based fuzzy control design for nonlinear interconnected systems is characterized in terms of solving an eigenvalue problem (EVP) with five prespecified scalars for each subsystem. In general, it is a difficult task to solve the EVP with five prespecified scalars. Fortunately, this special EVP can be easily solved by using a genetic algorithm and an LMI-based optimization method. Finally, a simulation example is given to illustrate the design procedure and robust performance of the proposed methods.