15 research outputs found

    Observer-based sliding mode control for stabilization of a dynamic system with delayed output feedback

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    This paper considers the sliding mode control problem for a kind of dynamic delay system. First by utilizing Lyapunov stability theory and a linear matrix inequality technique, an observer based on delayed output feedback is constructed. Then, an integral sliding surface is presented to realize the sliding mode control for the system with the more available stability condition. Finally, some numerical simulations are implemented to demonstrate the validity of the proposed control method.Bo Wang, Peng Shi, Hamid Reza Karimi, and Cheng Chew Li

    Fuzzy variable structure control for uncertain systems with disturbance

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    This paper focuses on the fuzzy variable structure control for uncertain systems with distrubance. Specifically, the fuzzy control is introduced to estimate the control disturbance, the switching control is included to compensate for the approximation error, and they possess the characteristic of simpleness in design and effectiveness in attenuating the control chattering. Some typical numerical examples are presented to demonstrate the effectiveness and advantage of the fuzzy variable structure controller proposed.Bo Wang, Peng Shi, Hamid Reza Karimi, Jun Wang and Yongduan Son

    A Two-Wheeled Self-Balancing Robot with the Fuzzy PD Control Method

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    A two-wheeled self-balancing robot with a fuzzy PD control method is described and analyzed as an example of a high-order, multiple-variable, nonlinear, strong-coupling, and unstable system. Based on a system structure model, a kinetic equation is constructed using Newtonian dynamics and mechanics. After a number of simulation experiments, we get the best , , and state-feedback matrices. Then a fuzzy PD controller is designed for which the position and speed of the robot are inputs and for which the angle and angle rate of the robot are controlled by a PD controller. Finally, this paper describes a real-time control platform for the two-wheeled self-balancing robot that controls the robot effectively, after some parameter debugging. The result indicates that the fuzzy PD control algorithm can successfully achieve self-balanced control of the two-wheeled robot and prevent the robot from falling

    Local Stabilization of Time-Delay Nonlinear Discrete-Time Systems Using Takagi-Sugeno Models and Convex Optimization

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    A convex condition in terms of linear matrix inequalities (LMIs) is developed for the synthesis of stabilizing fuzzy state feedback controllers for nonlinear discrete-time systems with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is used to represent exactly the nonlinear system in a restricted domain of the state space, called region of validity. The proposed stabilization condition is based on a Lyapunov-Krasovskii (L-K) function and it takes into account the region of validity to determine a set of initial conditions for which the actual closed-loop system trajectories are asymptotically stable and do not evolve outside the region of validity. This set of allowable initial conditions is determined from the level set associated to a fuzzy L-K function as a Cartesian product of two subsets: one characterizing the set of states at the initial instant and another for the delayed state sequence necessary to characterize the initial conditions. Finally, we propose a convex programming problem to design a fuzzy controller that maximizes the set of initial conditions taking into account the shape of the region of validity of the T-S fuzzy model. Numerical simulations are given to illustrate this proposal

    Almost sure H∞ sliding mode control for nonlinear stochastic systems with Markovian switching and time-delays

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    This paperinvestigatesthealmostsure H1 sliding mode control (SMC) problem for non linear stochastic systems with Markovian switching and time-delays. An integral sliding surface is first constructed for the addressed system. Then, by employing the topping time method combined with martingale in equalities, sufficient conditions are established to ensure the almost surely exponential stability and the H 1 performance of the system dynamics in the specified sliding surface. ASMC law is designed to guarantee the reach ability of the specified sliding surface almost surely. Furthermore, the obtained results are applied to a class of special nonlinear stochastic systems with Markovian switching and time-delays, where the desired SMC law is obtained in terms of the solutions to a set of matrix in equalities. Finally, a numerical example is given to show the effectiveness of the proposed SMC scheme

    Fuzzy sliding mode control design for a class of disturbed systems

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    This paper discusses the problem of the fuzzy sliding mode control for a class of disturbed systems. First, a fuzzy auxiliary controller is constructed based on a feedback signal not only to estimate the unknown control term, but also participates in the sliding mode control due to the fuzzy rule employed. Then, we extend our theory into the cases, where some kind of system information can not be obtained, for better use of our theoretical results in real engineering. Finally, some typical numerical examples are included to demonstrate the effectiveness and advantage of the designed sliding mode controller. © 2013 The Franklin Institute.Bo Wang, Peng Shi, Hamid Reza Karim

    Intelligent Power Sharing of DC Isolated Microgrid Based on Fuzzy Sliding Mode Droop Control

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    A New Fuzzy System Based on Rectangular Pyramid

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    A new fuzzy system is proposed in this paper. The novelty of the proposed system is mainly in the compound of the antecedents, which is based on the proposed rectangular pyramid membership function instead of t-norm. It is proved that the system is capable of approximating any continuous function of two variables to arbitrary degree on a compact domain. Moreover, this paper provides one sufficient condition of approximating function so that the new fuzzy system can approximate any continuous function of two variables with bounded partial derivatives. Finally, simulation examples are given to show how the proposed fuzzy system can be effectively used for function approximation
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