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State estimation based on fractional order sliding mode observer method for a class of uncertain fractional-order nonlinear systems

机译:基于分数阶滑模观测器方法的一类不确定分数阶非线性系统的状态估计

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State estimation of dynamic systems is quite significant in many research areas, such as state-based control and stabilization, state-based monitoring and fault detection. This paper is concerned with the problem of observer-based state estimation for a class of fractional-order (FO) nonlinear dynamic systems. The objective is to consider the state estimation of FO nonlinear system with the sliding mode control (SMC) technique, and conduct the asymptotic stability analysis for the estimate error dynamic system. Firstly, the considered FO nonlinear system models with constant and uncertain parameters are both presented. Fractional order sliding mode observer (FOSMO) structures are established for the FO nonlinear system models. Then, the asymptotic stability of the estimate error dynamic systems are analyzed via employing the Lyapunov stability analysis method for FO systems, and the sufficient conditions of asymptotic stability are derived. FOSMOs design for FO nonlinear systems of Caputo's and Riemann-Liouville's differential operators are both investigated, and the corresponding asymptotic stability sufficient conditions of the error dynamic systems are presented to insure the estimation accuracy of FOSMOs. Finally, multiple simulation examples are provided to demonstrate the effectiveness of the presented FOSMOs.
机译:动态系统的状态估计在许多研究领域都非常重要,例如基于状态的控制和稳定,基于状态的监视和故障检测。本文涉及一类分数阶(FO)非线性动力学系统的基于观测器的状态估计问题。目的是考虑采用滑模控制(SMC)技术对FO非线性系统进行状态估计,并对估计误差动态系统进行渐近稳定性分析。首先,给出了考虑的具有恒定和不确定参数的FO非线性系统模型。针对FO非线性系统模型建立了分数阶滑模观测器(FOSMO)结构。然后,采用FO系统的Lyapunov稳定性分析方法,对估计误差动态系统的渐近稳定性进行了分析,得到了充分的渐近稳定性条件。分别研究了Caputo和Riemann-Liouville微分算子的FO非线性系统的FOSMOs设计,并给出了误差动态系统的相应渐近稳定性充分条件,以确保FOSMOs的估计精度。最后,提供了多个仿真示例来演示所提出的FOSMO的有效性。

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