A team theoretic approach to decentralized control of systems with stochastic parameters

Research output: Contribution to journalConference article

Abstract

This paper investigates an optimal decentralized control problem for a system with B-matrices dependent on stochastic parameters. It is assumed that these parameters are independent in time and available locally to each controller. The objective is to find a decentralized state feedback control policy that minimizes a multi step quadratic cost function. We first solve this problem for the case of one time step and show that the optimal policy can be reached through iterating the best responses of each player. For the optimal multiple step problem, a dynamic programming approach is employed while using the result of the one step control at each step. Finally in the infinite horizon case, we provide sufficient conditions under which the optimal control policy is unique and stabilizes the system in a mean square sense.

Original languageEnglish (US)
Article number6425872
Pages (from-to)2116-2121
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

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Decentralized control
Decentralized Control
Control Policy
Optimal Policy
Optimal Control
State Feedback Control
Infinite Horizon
Quadratic Function
State feedback
Dynamic programming
Cost functions
Mean Square
Decentralized
Feedback control
Dynamic Programming
Cost Function
Control Problem
Minimise
Controller
Controllers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

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abstract = "This paper investigates an optimal decentralized control problem for a system with B-matrices dependent on stochastic parameters. It is assumed that these parameters are independent in time and available locally to each controller. The objective is to find a decentralized state feedback control policy that minimizes a multi step quadratic cost function. We first solve this problem for the case of one time step and show that the optimal policy can be reached through iterating the best responses of each player. For the optimal multiple step problem, a dynamic programming approach is employed while using the result of the one step control at each step. Finally in the infinite horizon case, we provide sufficient conditions under which the optimal control policy is unique and stabilizes the system in a mean square sense.",
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AB - This paper investigates an optimal decentralized control problem for a system with B-matrices dependent on stochastic parameters. It is assumed that these parameters are independent in time and available locally to each controller. The objective is to find a decentralized state feedback control policy that minimizes a multi step quadratic cost function. We first solve this problem for the case of one time step and show that the optimal policy can be reached through iterating the best responses of each player. For the optimal multiple step problem, a dynamic programming approach is employed while using the result of the one step control at each step. Finally in the infinite horizon case, we provide sufficient conditions under which the optimal control policy is unique and stabilizes the system in a mean square sense.

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