汇报标题 (Title)：Pontryagin’s maximum principle, optimal control problem solver RIOTS_95, machine learning and fractional calculus (庞特里亚金极大值道理，最优节造问题求解器RIOTS_95, 机械进建和分数阶微积分)
汇报人 (Speaker)：陈乌海 教授（University of California, Merced, USA）
汇报功夫 (Time)：2023年12月1日(周五) 11:00
汇报地址 (Place)：腾讯会议(363-278-420)
约请人(Inviter)：李常品、蔡敏
主办部门：理学院数学系
汇报提要：This seminar is of tutorial nature to inspire research efforts in connecting optimal control (OC) and machine learning (ML) and fractional calculus (FC). First, a tutorial on static and dynamic optimization problems is presented with a uniform Lagrangian multiplier framework. After a simple exposure to calculus of variation (COV) and its transversality conditions, we derive the basic solution based on Hamiltonian and the Pontryagin’s maximum principle (PMP). An analytical simplest example is presented to show the need of a general-purpose toolbox to solve OCPs (optimal control problems). Then RITOS_95, a general OCP solver in the form of a Matlab toolbox is introduced with some solved example OCPs. Live OCP solving runs in Matlab will be shown.
