Art Krener, Feb 2016
Art Krener will be visiting Caltech on 18 Feb (Thu). If you would like to meet with him, sign up below.
- ~10:15 - Richard Murray, 109 Steele Lab
- 10:45 - set up for seminar
- 11:00 - Seminar, 115 Gates-Thomas
- 12:00 - Lunch with Richard, Doug
- 1:30 - Ivan Papusha, 231 Annenberg
- 2:15 - Yoke Peng, 230 Annenberg
- 3:00 - Doyle
- 3:45 - Stop by Richard's office on the way out
Adaptive Horizon Model Predictive Control
Arthur J. Krener, Naval Postgraduate School
18 Feb (Thu) - 11:00am PST, 115 Gates-Thomas
Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.