6 research outputs found

    Model reduction design for continuous systems with finite frequency specifications

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    This paper is concerned with the problem of model reduction design for continuous systems in Takagi-Sugeno fuzzy model. Through the defined FF H∞ gain performance, sufficient conditions are derived to design model reduction and to assure the fuzzy error system to be asymptotically stable with a FF H∞ gain performance index. The explicit conditions of fuzzy model reduction are developed by solving linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the proposed method

    Fuzzy PD Control of Networked Control Systems Based on CMAC Neural Network

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    The network and plant can be regarded as a controlled time-varying system because of the random induced delay in the networked control systems. The cerebellar model articulation controller (CMAC) neural network and a PD controller are combined to achieve the forward feedback control. The PD controller parameters are adjusted adaptively by fuzzy reasoning mechanism, which can optimize the control effect by reducing the uncertainty caused by the network-induced delay. Finally, the simulations show that the control method proposed can improve the performance effectively

    Global Stabilization of High-Order Time-Delay Nonlinear Systems under a Weaker Condition

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    Under the weaker condition on the system growth, this paper further investigates the problem of global stabilization by state feedback for a class of high-order nonlinear systems with time-varying delays. By skillfully using the homogeneous domination approach, a continuous state feedback controller is successfully designed, which preserves the equilibrium at the origin and guarantees the global asymptotic stability of the resulting closed-loop system. A simulation example is given to demonstrate the effectiveness of the proposed design procedure

    Model Reduction of Discrete-time Interval Type-2 T-S Fuzzy Systems

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    Extended Dissipative Filter for Delayed T-S Fuzzy Network of Stochastic System with Packet Loss

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    This research investigates a time-varying delay-based adaptive event-triggered dissipative filtering problem for the interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy networked stochastic system. The concept of extended dissipativity is used to solve the ,  and dissipative performances for (IT-2) T-S fuzzy stochastic systems in a unified manner. Data packet failures and latency difficulties are taken into account while designing fuzzy filters. An adaptive event-triggered mechanism is presented to efficiently control network resources and minimise excessive continuous monitoring while assuring the system’s efficiency with extended dissipativity. A new adaptive event triggering scheme is proposed which depends on the dynamic error rather than pre-determined constant threshold. A new fuzzy stochastic Lyapunov-Krasovskii Functional (LKF) using fuzzy matrices with higher order integrals is built based on the Lyapunov stability principle for mode-dependent filters. Solvability of such LKF leads to the formation of appropriate conditions in the form of linear matrix inequalities, ensuring that the resulting error mechanism is stable. In order to highlight the utility and perfection of the proposed technique, an example is presented

    Movement Control in Recovering UUV Based on Two-Stage Discrete T-S Fuzzy Model

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    A two-stage discrete T-S fuzzy model controller, which is formed by a motion controller and a dynamic controller connected in series, is presented to solve UUV (unmanned underwater vehicle) movement control problem for recovering. The motion controller is designed based on the uncertain T-S model and the concept of discrete fuzzy vector. The position error between UUV and moving platform as the input of the motion controller is converted into the speed commands of UUV at the next time. The dynamic controller design is based on the theory of fuzzy region model and a relaxed condition for Lyapunov stabilization function is derived in the form of linear matrix inequalities, which generate force and torque required to complete the recovery task. The feasibility and the efficiency of the proposed control scheme are illustrated through the simulations that UUV follows moving platform
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