Title :
Decentralized Adaptive Optimal Control of Large-Scale Systems With Application to Power Systems
Author :
Tao Bian ; Yu Jiang ; Zhong-Ping Jiang
Author_Institution :
Dept. of Electr. & Comput. Eng., New York Univ., New York, NY, USA
Abstract :
This paper studies the optimal control problem for large-scale systems with unknown parameters and dynamics. By using robust adaptive dynamic programming (RADP) method, a decentralized optimal control design is given for large-scale systems with unmatched uncertainties. The convergence of the proposed RADP algorithm and the asymptotic stability of the closed-loop large-scale system are studied rigorously. Finally, a numerical example of a large-scale power system is adopted to illustrate the effectiveness of the obtained algorithm.
Keywords :
adaptive control; asymptotic stability; closed loop systems; decentralised control; dynamic programming; optimal control; power system control; robust control; RADP algorithm; RADP method; asymptotic stability; closed-loop large-scale system; decentralized adaptive optimal control; decentralized optimal control design; optimal control problem; power systems; robust adaptive dynamic programming method; Algorithm design and analysis; Bismuth; Decentralized control; Heuristic algorithms; Large-scale systems; Optimal control; Power system stability; Adaptive dynamic programming (ADP); adaptive optimal control; power systems;
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2014.2345343