WorkshopThe workshops will be held at 13:00-17:30 on June 9, 2019.
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/
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
Title: Nonlinear Real-time Optimal Control using MPSP: A New Fast MPC Paradigm
Organizers: Radhakant Padhi (Indian Institute of Science)
Abstract: The main objective of this workshop will be to expose and equip the participants with the recently-developed computationally efficient Model Predictive Static Programming (MPSP) and its several extensions. Like model predictive control (MPC), a model-based prediction-correction approach is adopted in MPSP. However, the entire problem is converted to a very low-dimensional "static programming" problem, from which the control history update is computed in closed-form (i.e. without the need of an optimization solver). Moreover, the necessary sensitivity matrices (which are the backbone of the algorithm) are computed recursively. These two key innovations make the process computationally quite efficient, thereby making it suitable for implementation in real-time. Details of this promising MPSP algorithm, along with several extensions which make it applicable for a wide class of problems, will be discussed in this workshop. A number of challenging real-life application problems in aerospace, mobile robotics and process control will be discussed to demonstrate the applicability of MPSP for trajectory planning and trajectory tracking of nonlinear systems in real-time. A generic MATLAB function about the basic MPSP technique developed by the instructor will be distributed to the participants to enable them getting started quickly. Copies of several recent journal publications of the instructor will also be distributed. A brief overview of the basics of static optimization and optimal control theory will be included. No prior knowledge on optimal control and/or MPC is necessary to attend this workshop.
Keywords: Optimal Control and Optimization; Predictive Control; Aerospace Engineering
More information: Details
Title: Recent advances on measurement and control applications in agriculture and forestry
Organizers: Yuichi Chida (Shinshu University), Michihisa Iida (Kyoto University), Masami Iwase (Tokyo Denki University), Masaki Takahashi (Keio University), Ayanori Yorozu (Keio University)
Abstract: Measurement and control technologies greatly progress in agriculture and forestry. Especially, the progress of the autonomous control technologies of ground vehicles is remarkable and they are applied to development of an automatic combine as well as a multi-purpose agriculture robot. And also, automatic harvesting techniques for soft vegetables such as spinach and lettuce have been developed and automatic harvesters for such kind of vegetables have been proposed by using feedback control. Furthermore, some challenges on application of a drone in forestry field for measurement of some kind of forest environment information has been carried out. The goal of the workshop is to provide an introduction on measurement and control application to agriculture and forestry and to introduce challenging research problems in these fields.
Keywords: Mechatronics; Robotics and Motion Control; Control Applications
More information: TBD