Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


Control Design with Uncertain Predictions in Autonomous Systems: Theory and Practice

Forecasts will play an increasingly important role in the next generation of autonomous and semi-autonomous systems. In nominal conditions, predictions of system dynamics, human behavior and environment al envelope can be used by the control algorithm to improve safety and performance of the resulting system. However, in practice, constraint satisfaction, performance guarantees and real-time computation are challenged by the (1) growing complexity of the engineered system, (2) uncertainty in the human/machine interaction and (3) uncertainty in the environment where the system operates. In this talk I will present the theory and tools that we have developed over the past ten years for the systematic design of predictive controllers for uncertain linear and nonlinear systems. I will first provide an overview of our theoretical efforts. Then, I will focus on our recent results in addressing constraint satisfaction and real-time computation in large-scale networked systems. Throughout the talk I will use two applications to motivate our research and show the benefits of the proposed techniques: Safe Autonomous Cars and Green Intelligent Buildings. More info on:

Type of Seminar:
Lecture Series on Directions in Systems and Control
Prof. Francesco Borrelli
Mechanical Engineering, University of California, Berkeley, USA
Jan 26, 2012   17:15

ETZ E6, Gloriastrasse 35
Contact Person:

File Download:

Request a copy of this publication.
Biographical Sketch:
Francesco Borrelli received the `Laurea' degree in computer science engineering in 1998 from the University of Naples `Federico II', Italy. In 2002 he received the PhD from the Automatic Control Laboratory at ETH-Zurich, Switzerland. He is currently an Associate Professor at the Department of Mechanical Engineering of the University of California at Berkeley, USA. He is the author of more than seventy publications in the field of predictive control. He is author of the book Constrained Optimal Control of Linear and Hybrid Systems published by Springer Verlag, the winner of the 2009 NSF CAREER Award. In 2008 he was appointed the chair of the IEEE technical committee on automotive control. His research interests include constrained optimal control, model predictive control and its application to advanced automotive control and energy efficient building operation.