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Non-asymptotic and robust estimation for a class of nonlinear fractional-order systems
Communications in Nonlinear Science and Numerical Simulation ( IF 3.9 ) Pub Date : 2022-07-30 , DOI: 10.1016/j.cnsns.2022.106752
Chang Liu , Da-Yan Liu , Driss Boutat , Yong Wang , Ze-Hao Wu

This paper aims to deal with the non-asymptotic and robust estimation problem for nonlinear fractional-order systems. The motivation starts with a physical system which develops into a group of system models including linear and nonlinear, commensurate and noncommensurate, integer-order and noninteger-order ones. Different from the existing modulating functions method, the proposed method breaks through the limitation of transforming the original system into the input–output differential equation, which makes the estimation for more types of systems possible. By introducing a new class of fractional order modulating functions, the state is exactly expressed by algebraic integral formulas without knowing the initial conditions of the studied system, despite the corrupting noises in the output measurement. Finally, it is illustrated in the simulation examples that the proposed estimator not only proves to be effective in the state estimation of noninteger-order systems, but also shows its advantages in that of integer-order systems compared to the high-gain observer.



中文翻译:

一类非线性分数阶系统的非渐近鲁棒估计

本文旨在解决非线性分数阶系统的非渐近和鲁棒估计问题。其动机始于一个物理系统,该系统发展为一组系统模型,包括线性和非线性、相当和非相当、整数阶和非整数阶模型。与现有的调制函数方法不同,该方法突破了将原始系统转化为输入-输出微分方程的局限,使得对更多类型系统的估计成为可能。通过引入一类新的分数阶调制函数,尽管输出测量中存在破坏性噪声,但在不知道所研究系统的初始条件的情况下,可以用代数积分公式精确地表示状态。最后,

更新日期:2022-07-30
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