Quantized dissipative control based on T-S fuzzy model for wind generation systems

Stabilization analysis of fractional-order nonlinear permanent magnet synchronous motor model via interval type-2 fuzzy memory-based fault-tolerant control scheme

The main objective of this study is to improve the convergence rate performance and analyze the stability properties of the FOPMSM model considering the load-torque external disturbances and actuator faults. Due to the complex nonlinearity, the presented FONPMSM model in the d-q frame is approximated by an IT-2 T-S fuzzy modeling technique. Besides, the fuzzy memory-based FTC is designed to eliminate the typical characteristics of chaotic behaviors and stabilize the proposed nonlinear model even if load torque disturbances, actuator faults in the controller, and time delays occur. Further, by employing the fractional order-based fuzzy LKF, some sufficient conditions are carried out in terms of LMIs to guarantee the asymptotic stability conditions, and simultaneously, disturbance reduction is confirmed. And then, the desired control gain matrices are determined from solvable LMIs, which can help to enhance the system stability performance. Finally, the numerical simulation of T-S fuzzy-based FOPMSM model is given to validate the applicability and efficiency of the proposed controller.

Stability analysis for delayed T-S fuzzy systems: A compensation Lyapunov-Krasovskii functional method combined with free-weighting matrices

A compensation Lyapunov-Krasovskii functional (LKF) method combined with free-weighting matrices is presented to analyze the stability of delayed Takagi-Sugeno fuzzy systems. Firstly, the fuzzy LKF containing membership functions is constructed. Then, the compensation LKF method is presented to introduce the common double and triple integral terms to compensate the single and double integral terms related to the membership functions' derivatives, respectively, which arise in the derivative of the fuzzy LKF. Consequently, following the feature of the membership functions' derivatives, the fuzzy zero equations containing free-weighting matrices of integral terms are proposed to improve the relaxation quality in fuzzy integral terms. Resultantly, the stability criteria with less conservativeness are yielded. Moreover, the conservatism is reduced further by establishing the relaxed fuzzy LKF. Finally, the numerical example is employed to verify the merits of the presented method.

Fuzzy event-triggered tracking control for nonlinear unreliable networked systems

This article addresses a fuzzy event-triggered tracking control problem of unreliable networked systems. An event-based tracking controller is put forward to control the plant in fuzzy form. The looped Lyapunov-Krasovskii functional method is made use of conducting stability analysis, and sufficient conditions on the controller are determined. As a result, the tracking control performance is achieved for the controlled system. The feasibility of the presented tracking control design is verified by some examples.