Wen-Hua Chen, 4-21 Oct 2022

Professor Wen-Hua Chen from the University of Loughborough will visit Caltech on 4-21 Oct 2022. A schedule for the first few days of his visit is given below. Please feel free to sign up for any open times.

4 Oct (Tue) 8:30 am: Richard Murray, 109 Steele Lab 9:00 am: Soon-Jo Chung, 235 Guggenheim (including lab tour (CAST & ARCL)) 9:45 am: Diana Bohler (logistics) 10:30 am: Open 11:15 am: Open 12:00 pm: Lunch with Richard 1:15 pm: Houman Owhadi, 201 Steele House 2:00 pm: Lijun Chen, 217 Annenberg 2:45 pm: Andrew Taylor, 325 Annenberg 3:30 pm: Noel Csomay-Shanklin, 325 Annenberg 4:15 pm: Apurva (meet at 325 Annenberg and then walk over to 238 Annenberg or Annenberg lounge) 5:00 pm: Done for the day

5 Oct (Wed) 9:00 am: Ersin Das, Location: Steele House 9:45 am: Anushri Dixit, Location: Steele House 10:30 am: Open 11:15 am: Prithvi Akella, Location: Steele House 12:00 pm: Lunch 1:30 pm: Anima Anandkumar, 316 Annenberg 2:15 pm: Josefine Graebener, Annenberg Visiting Researcher Office 3:00 pm: CDS Tea, Annenberg 3:45 pm: Seminar - 121 Annenberg 5:00 pm: Break 6:00 pm: Dinner with NCS group (meet at 109 Steele Lab)

Stability of Optimisation-Based Control: Brief Review and New Results

Prof Wen-Hua Chen
Department of Aeronautical and Automotive Engineering
Loughborough University

With the increase of the size and the complexity of systems and their performance specifications, it is more difficult to find analytic solutions for a control system as in traditional approaches to give optimal performance. Model Predictive Control (MPC) provides a promising mechanism to realise numerical optimal solutions online to achieve best possible performance. However, establishing stability and other formal properties of this type of optimisation-based control imposes significant challenges. This talk starts with the brief overview of 30 years’ journey in developing stability theory for MPC. It points out that despite all the success, there is still a significant gap between available theoretic tools and practical applications. For example, a terminal cost that covers the optimal cost-to-go is, in general, required to add the cost function in order to ensure stability of a MPC algorithm, but most of MPC used in practical applications does not have a terminal cost (for example, all cases studies in Matlab Nonlinear MPC Toolbox do not have a terminal cost but work well). This talk presents a new approach and development in this area. The stability condition is entirely complementary to the existing terminal based MPC stability theory. Opposite to the existing MPC stability conditions, the new stability conditions cover the terminal cost being less than the optimal cost-to-go including zero terminal cost even negative. The new conditions are established based on a property of a modified stage cost. Numerical results are presented to illustrate the links and differences between the new approach and the existing stability theory. It is hoped that this work would trigger more research into understanding the interaction between optimisation and feedback loops in both the AI and the control community so ensure efficiency and safety of future robotics and autonomous systems.

Dr Wen-Hua Chen holds Professor in Autonomous Vehicles in the Department of Aeronautical and Automotive Engineering at Loughborough University, UK. Prof. Chen has a considerable experience in control, signal processing and artificial intelligence and their applications in aerospace, automotive and agriculture systems. In the last 15 years, he has been working on the development and application of unmanned aircraft system and intelligent vehicle technologies, spanning autopilots, situational awareness, decision making, verification, remote sensing for precision agriculture and environment monitoring. He is a Chartered Engineer, and a Fellow of IEEE, the Institution of Mechanical Engineers and the Institution of Engineering and Technology, UK. Recently Prof Chen was awarded an EPSRC (Engineering and Physical Science Research Council) Established Career Fellowship in developing control theory for next generation of control systems to enable high levels of automation such as robotics and autonomous systems.