学 术 报 告

报告题目:Modulating functions based non-asymptotic and robust fractional order differentiators

报告学者:Dr. Dayan LIU

报告者单位PRISME Laboratory Control Group, Central France



摘要:For cost and technological reasons, there always exist some variables and parameters, which cannot be measured. Moreover, the measurements usually contain noises. Sometime, fast estimations with convergence in finite-time are required in on-line applications. For these reasons, the modulating functions method originally introduced by Shinbrot in 1954 for system identification has been applied and extended in signal processing and automatic control, such as parameter estimation and numerical differentiation, etc. This method has the following advantages. Firstly, the obtained estimators are exactly given by integral formulae of the observation signal. Thus, they are algebraic and non-asymptotic. Fast estimation can be provided using sliding integration window with finite length. The knowledge of initial conditions is not needed and the derivatives of noisy signals don not need to be calculated. Moreover, thanks to the integrals in the formulae, they are robust with respect to corrupting noises without the need of knowing in priori their statistical properties. In this talk, it will be shown how to extend the modulating functions method to design fractional order differentiators in different situations by introducing the adapted modulating functions.

报告人简介:刘大研:法国中部大区PRISME实验室控制组副教授。主要研究领域有整数阶和分数阶系统的辨识和估计。于2011年获得了法国里尔大学应用数学博士学位,于2013年获得了法国中部卢瓦尔河谷国立应用科学学院副教授永久职位。2012年获得中国政府颁发的海外优秀自费留学生奖。2017年10月,被任命为国际自动控制联盟《线性控制系统》技术委员会成员,2019年1月,被任命为中国自动化学会分数阶系统与控制专业委员会委员,2019年5月,被任命为Fractal and Fractional杂志编委委员。