课程通知:“Fundamental Techniques in Optimization and Control” by Frank L. Lewis

课程通知:“Fundamental Techniques in Optimization and Control” by Frank L. Lewis

受东北大学流程工业综合自动化国家重点实验室邀请,美国德州大学阿灵顿分校Frank L. Lewis教授将在我校讲授短期课程。欢迎广大师生踊跃参加!
课程题目: Fundamental Techniques in Optimization and Control
时间:2016年5月9日(周一)、10日(周二)13:00 - 17:00
地点:东北大学建筑馆二楼会议室
Biography:
Frank L. Lewis, member, National Academy of Inventors. Fellow IEEE, Fellow IFAC, Fellow U.K. Institute of Measurement & Control, PE Texas, U.K. Chartered Engineer. UTA Distinguished Scholar Professor, UTA Distinguished Teaching Professor, and Moncrieff-O’Donnell Chair at the University of Texas at Arlington Research Institute. Qian Ren Thousand Talents Consulting Professor, Northeastern University, Shenyang, China. IEEE Control Systems Society Distinguished Lecturer.

Course Overview:
This 2 day short course will cover basic principles of optimization and optimal control design. The textbook is
F.L. Lewis, D. Vrabie, and V. Syrmos, Optimal Control, third edition, John Wiley and Sons, New York, 2012.
The course presents the basic precepts of optimal control design for linear and nonlinear processes. Discrete-time and continuous-time designs complement each other and both are covered. The key ideas of system Hamiltonian function, costate, and calculus of variations are detailed. Key robustness properties of optimal design are covered. Differential games will be covered, including zero-sum games and multiplayer non-zero-sum games. We will present reinforcement learning methods to learn optimal control solutions online in real time using measured data. First we cover discrete-time RL and approximate dynamic programming (ADP. Then continuous-time RL and Integral Reinforcement Learning (IRL). Some new techniques of off-policy RL will be covered that allow learning of optimal control solutions online with no knowledge of the system dynamics.
The course graduate will understand the essential principles of optimality and optimal control system design, including Riccati equations, Hamiltonian functions, Hamilton-Jacobi equations, the tracker problem, dynamic programming, and other topics essential to a full understanding of optimal control.