 |
ProfessorChongqing University, China |
Jiangshuai Huang received the B.Eng. and M.Sc. degrees in automation from Huazhong University of Science and Technology, Wuhan, China, in 2007 and 2009, respectively, and the Ph.D. degree from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 2015. He was a Research Fellow with the Department of Electricity and Computer Engineering, National University of Singapore from August 2014 to September 2016. He has been with the School of Automation, Chongqing University since October 2016, where he is currently a Full Professor. His research interests include adaptive control, nonlinear systems control, underactuated mechanical system control, and multiagent system control. Prof. Huang received Zhang Si-Ying Outstanding Youth Paper Award in the 25th Chinese Control and Decision Conference, the First Prize of Science and Technology Progress Award by Chinese Institute of Command and Control (CICC) in 2018, the First Prize of Natural Science Award by Government of Chongqing in 2020 and the First Prize of Natural Science Award by Chinese Association of Automation in 2021. He is an Associate Editor for the IEEE TRANSACTIONS ON CYBERNETICS and IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS.
Dynamic Surface Control with Nonlinear filters: with an Application to Underactuated Cranes
This talk introduces a nonlinear filter based dynamic surface control scheme with applications to the underactuated crane systems. The backstepping technique provides a systematic approach to obtain a control law designed step by step through a recursive procedure for nonlinear control across multiple classes of nonlinear systems, and the dynamic surface control (DSC) method addresses the issue of “explosion of complexity” and thus makes the backstepping control schemes applicable in many practical systems. However, there are serious technical issues for practical implementation in all the existing DSC approaches. 1) Determining the parameters of the filters is extremely difficult. 2) The closed-loop stability with the DSC method is only semi-global since the selection of parameters depends on the initial conditions of the system. 3) In the presence of unknown parameters, the traditional DSC method fails. To solve these problems, a nonlinear filter based dynamic surface control is introduced which involves constructing nonlinear filters such that the outputs of the filters can track the virtual control errors much faster and the tracking errors do not rely on the parameters. A new approach is provided as a guideline on designing the right nonlinear filters that can dominate the filter input with arbitrary positive filter parameters and simultaneously make the controller free from initial conditions, leading to a novel DSC method with the control parameters being free from the tedious calculation of various upper bounds. The new scheme enables the choice of control parameters in adaptive DSC, and finally it is applied to the adaptive stabilization control of a class of underactuated crane systems.