Professor lecture - Paolo Falcone, Electrical Engineering

Control Invariance in Intelligent Transportation Systems, with applications to vehicle lateral control and multi-vehicle systems
Seminar for the title of Professor by Chalmers University of Technology: Paolo Falcone in the Mechatronics research group, department of Electrical Engineering. 

Control invariance is a property of systems state sets, which is used in control design for constrained systems. If a system state trajectory starts in a control invariant set C, it will be always possible to find an admissible control input keeping the system state trajectory within C. Hence, if the system constraints are defined w.r.t. to the required performance (e.g., maximum accepted bounds on the tracking errors), control invariant sets can be used to design control laws with performance guarantees. In this talk, we will highlight some computational aspects related to control invariant sets and present recent results from their applications to a lateral vehicle dynamics control problem and to the control of a multi-vehicle system over a wireless network.

In Level-5 autonomous vehicles, a human driver will not be available to back up the vehicle control system anymore. Hence, the overall autonomous driving system should be designed in order to provide performance and safety guarantees. In this talk, we will consider the problem of designing a vehicle lateral motion control algorithm with guaranteed bounds on the lateral deviation from a desired path. Such a problem can be easily solved by resorting to Model Predictive Control (MPC) techniques, where a terminal control invariant set is needed to persistently guarantee that the deviation from the path is within the desired bound. Nevertheless, the complexity of the representation of such terminal control invariant sets can dramatically increase the resulting controller complexity. We will show how low-complexity invariant sets can be derived thanks to newly developed methods and how these can be used as an additional tuning tool to trade o the MPC controller complexity for the size of its feasibility set.

The next challenge, beyond high-level autonomous driving, is the cooperation of autonomous vehicles, which is expected to fully enable the potential of autonomous driving technologies and impact the society. Nevertheless, the safety and performance issues arising from the tight coupling between information losses and delays and the control system stability and performance must be accounted for at the design stage. Starting from a multi-vehicle coordination problem at trac junctions, which has been experimentally demonstrated, we will motivate a joint communication and control paradigm, where a central coordinator decides upon control inputs to a set of dynamical systems and their access to the communication channel. We will show a few results from numerical examples and new research directions.

Constrained control, Vehicle lateral control, Multi-vehicle systems, Networked control systems, Joint communication and control design
Category Public lecture
Location: EB, lecture hall, Hörsalsvägen 11, Campus Johanneberg
Starts: 27 August, 2018, 10:00
Ends: 27 August, 2018, 11:00

Published: Thu 05 Jul 2018. Modified: Fri 24 Aug 2018