Workshop

The workshops will be held at 13:00-17:30 on June 9, 2019.

WS1

Place: Conference Room 22

Title: Real-Time Algorithms and Applications of Nonlinear Model Predictive Control

Organizers: Toshiyuki Ohtsuka (Kyoto University)

Abstract: In nonlinear model predictive control (NMPC), a nonlinear optimal control problem over a finite future is solved at each sampling time, and the initial value of the optimal control is used as the actual control input to the system, which results in a kind of state feedback. NMPC can deal with a wide variety of control problems as long as the nonlinear optimal control problem can be solved in real time, i.e., within the sampling period of the feedback control system. Real-time algorithms for NMPC and their applications have been active areas of research for more than a decade. The goal of this workshop is to provide an overview of this field and to introduce challenging directions of research such as applications to fast systems or complicated problems and parallel computation.

Keywords: Predictive Control; Optimal Control and Optimization; Automotive Systems

More information: http://www.ids.sys.i.kyoto-u.ac.jp/ASCC2019WS1/

WS2

Place: International Conference Room

Title: Reinforcement Learning and Control

Organizers: Wei-Yu Chiu (National Tsing Hua University)

Abstract: This workshop intends to present a tutorial on the interaction of reinforcement learning (RL) and control and some advanced topics on the associated applications. During the workshop duration, background of RL is given first; basic building blocks of RL such as Markov decision process, Bellman equations, value iteration and policy iteration are introduced; the relationship between RL and control is investigated from the perspectives of linear quadratic regulation, differential dynamic programming, and linear quadratic Gaussian; a few online resources related to RL based control are presented; three advanced topics on RL and control are given: 1) human-in-the-loop learning using inverse RL, 2) deep RL for robot control, and 3) risk assessment and nursing assistant using deep RL. The theme of this workshop is timely and considered as one application of machine learning, a subfield of artificial intelligence. The workshop will provide opportunities for attendees from different research areas (such as control, optimization, and machine learning) to meet each other, network and share best practices in the research of RL and control.

Keywords: AI and Expert Systems; Control Applications

More information: https://www.ee.nthu.edu.tw/wychiu/ASCC2019.htm

WS3

WS3 was cancelled.

WS4

WS4 was cancelled.