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In this paper, the fuzzy c-regression model of the lithium battery and its application to the estimation of the state of charge (SOC) is proposed. We apply the fuzzy c-regression models (FCRM) to formulate the parameters in the equivalent circuit model (ECM) of the lithium battery. Based on these fuzzy c-regression models, we can estimate the SOC of the given lithium battery. The direct current internal...
In this paper, the fuzzy c-regression model of the lithium battery and its application to the estimation of the state of charge (SOC) is proposed. The equivalent circuit model (ECM) of the lithium battery as shown in fig. 1 is adopted. It is seen that all the parameters, VOC, Rt, Rp, and Cp, in the ECM depend on the SOC of the lithium battery. Thus, we apply the fuzzy c-regression models (FCRM) to...
In this paper, the estimation of the state of charge (SOC) of lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm is proposed. Based on these experiment data, we apply the FCRM clustering algorithm with affine linear functional cluster representatives to build the dynamic behavior of all parameters for the RC model. Finally, the simulation results demonstrate the effectiveness...
In this paper, the problem of estimating the asymptotic stability region (ASR) of uncertain nonlinear systems is considered. Our approach is based on Takagi-Sugeno (T-S) fuzzy model and variable structure control (VSC) technique. To simplify the problem, we use a state transformation to reduce the system order of the T-S fuzzy systems. Then we design the sliding surface for the transformed system...
This paper deals with the control problem of a class of discrete time systems with multiple input delays. By using a state transformation approach, the discrete time system with multiple input delays can be transformed into an equivalent linear system with free of input delays. Based on the equivalent linear system, a quasi-sliding mode controller is presented for the discrete-time system with multiple...
This paper addresses the problem of adaptive fuzzy integral sliding mode control (AFISMC) for uncertain nonlinear systems with state and input delays. First, we employ a state-transformation to map the nonlinear system into an input-delay free system. Then, an adaptive fuzzy technique is applied to estimate the bound of the lumped perturbation. Finally, based on Lyapunov stability theorem, a controller...
In this paper, an observer-based robust adaptive fuzzy sliding mode controller (RAFSMC) for an unknown nonlinear dynamical system with dead-zone input is presented. First, the fuzzy models are used to estimate the unknown function of the nonlinear dynamical system. Next, an observer is employed to estimate the tracking error. By the strictly-positive-real (SPR) Lyapunov stability theorem, it is shown...
This paper addresses the problem of model reference adaptive fuzzy sliding mode controller (MRAFSMC) for uncertain time-delay systems with input containing sector nonlinearities and dead-zone. The model reference tracking control design method and the adaptive fuzzy sliding mode control technique are combined in the design of the MRAFSMC. By the Lyapunov stability theorem, it is shown that the proposed...
In this paper, the design of a model reference adaptive fuzzy sliding mode controller (MRAFSMC) for a class of time-delay uncertain nonlinear systems with input containing sector nonlinearities and dead-zone is investigated. First, an adaptive fuzzy technique is applied to estimate the bound of the lumped uncertainties. Next, based on the Lyapunov stability theorem, a MRAFSMC is developed to solve...
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