题    目:Compromises in Control Design- A Multi-Objective Optimization View

时    间:2018年3月27日  上午9:00 

地    点:交通楼727

报告人:Jian-Qiao Sun  孙建桥, Professor, 国家千人计划教授, Ph.D., P.E., ASME Fellow,School of EngineeringUniversity of CaliforniaMerced, CA 95343, U.S.A.

Abstract

In this talk, we discuss various conflicting performance objectives or requirements for control design.  The performance of the closed-loop system is a function of various system and control parameters.  The quantitative design using multiple parameters to meet multiple conflicting performance objectives is a challenging task.  We review the method of multi-objective optimization for quantitative design of controls and discuss the evolutionary algorithm and cell mapping hybrid method for solving the multi-objective optimization problem.  We also illustrate the advanced algorithms of the parallel cell mapping methods with sub-division techniques.  Interesting examples of linear and nonlinear controls, and autonomous vehicle control are presented.

Speaker

Dr. Jian-Qiao Sun earned a BS degree in Solid Mechanics from Huazhong University of Science and Technology in Wuhan, China in 1982, a MS and a PhDin Mechanical Engineering from University of California at Berkeley in 1984 and 1988.  He worked for Lord Corporation at their Corporate R&D Center in Cary, North Carolina.  In 1994, Dr. Sun jointed the faculty in the department of Mechanical Engineering at the University of Delaware as an Assistant Professor, was promoted to Associate Professor in 1998 and to Professor in 2003. He joined University of California at Merced in 2007, and is currently a professor and chair of the department of Mechanical Engineering in School of Engineering.  He was elected to be a Qian-Ren-Ji-Hua scholar in the fourth cycle with Tianjin University.  Besides many other editorial experiences, he is the Editor-in-Chief of International Journal of Dynamics and Control published by Springer.

Hisresearch interests include stochastic non-linear dynamicsand control, cell mappingmethods, multi-objective optimization, energy harvestingand data-driven energy management of office building HVAC systems.