Optimal Collaborative Control in the Absence of Communication

Abstract:

In this talk, we consider a fully decentralized cooperative control problem with two dynamically decoupled agents. The objective is to design a state-feedback controller for each agent such that a global quadratic cost is minimized. No communication, explicit or implicit, is permitted between the agents or their controllers. The only sources of coupling are the cost function and the process noise. Our main result is an explicit and generically minimal state-space construction of the optimal controller. A surprising feature of the optimal controller is that it is dynamic, and it has a number of states that scales with the rank of the covariance between the process noise of each agent. The key step in the solution is a novel decomposition of the noise covariance matrix, which splits the convex program associated with the decentralized controller synthesis into simpler centralized problems that can be solved separately.

Presentation Slides

Biography:Laurent Lessard is a post doctoral researcher at LTH in Lund, Sweden. His research interests include decentralized control, optimization, and computationally tractable approaches for complex engineering applications. Prior to coming to LTH, he received the BASc degree in Engineering Science at the University of Toronto in 2003, and the PhD degree from Stanford University in 2011.