Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 29, Issue 10, Pages 2902-2915Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2020.3009729
Keywords
Sliding mode control; Fuzzy systems; Detectors; Symmetric matrices; Communication networks; Stability analysis; Heuristic algorithms; Dynamic event-triggered mechanism (DETM); Markovian jump systems (MJSs); sliding mode control (SMC); T-S fuzzy model
Funding
- NNSF [61673174, 61803255]
- 111 Project from China [B17017]
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In this article, the sliding mode control problem for a class of Markovian jump systems is addressed using the T-S fuzzy model. A dynamic event-triggered strategy is introduced to reduce the frequency of state transmission and a mode detector is utilized to estimate the unavailable system mode. The proposed detected-mode-dependent event-triggered sliding mode controller relaxes the conditions on reachability and stability conditions by constructing a relation on the membership functions between the fuzzy model and the controllers.
In this article, the sliding mode control (SMC) problem is addressed for a class of Markovian jump systems via the T-S fuzzy model. First, in order to reduce the frequency of state transmission for alleviating congestion phenomenon in the bandwidth-limited communication network, a dynamic event-triggered (DET) strategy is introduced into the sensor-to-controller channel, in which an additional internal dynamical variable is employed to adjust the event-triggered condition adaptively. A fundamental issue resulting from the event-triggered strategy is that the controller cannot obtain the information about system mode during the triggering interval. Aiming at the phenomenon, this work utilizes a mode detector to estimate the unavailable system mode. Then, this article proposes a detected-mode-dependent event-triggered sliding mode controller whose membership grades are determined only via the transmitted state at the triggering instant. By constructing a relation on the membership functions (MFs) between the fuzzy model and the controllers for MF-dependent analysis, the conditions on the reachability and stability conditions are relaxed. Furthermore, an optimization algorithm is provided for the minimum control power via a high-dimensional grid searching for the coefficients of the internal dynamic variables, which, together with the designed detected-mode-dependent sliding mode controller, constitutes the novel SMC scheme under the DET strategy. Finally, the simulation results via the single-link arm system are provided to illustrate the efficiency of the proposed method.
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