Optimal Control Design under Structured Model Information Limitation Using Adaptive Algorithms
2012 (English)Article in journal (Refereed) Submitted
Networked control strategies based on limited information about the plant model usually results in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. In this paper, we show that with an adaptive networked controller with limited plant model information, it is indeed possible to achieve a competitive ratio equal to one. We show that an adaptive controller introduced by Campi and Kumar asymptotically achieves closed-loop performance equal to the optimal centralized controller with full model information. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed loop performance measure is the ergodic mean of a quadratic function of the state and control input. We illustrate the applicability of the results numerically on a vehicle platooning problem.
Place, publisher, year, edition, pages
Interconnected systems, Adaptive Control, Optimal Control, Structural Constraints
IdentifiersURN: urn:nbn:se:kth:diva-141486OAI: oai:DiVA.org:kth-141486DiVA: diva2:697236
QS 20152014-02-172014-02-172015-03-27Bibliographically approved