Stochastic adaptive one-step-ahead optimal controllers based on input matching

Optimal adaptive controller based on the ELS algorithm is established using the input matching technique. The control signal is reduced to a constant weighted sum of the measurable information-state vector components using a one-step-ahead quadratic cost function to govern the behavior of the stocha...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 45; no. 5; pp. 980 - 983
Main Authors Lo, Kueiming, Zhang, Dachun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2000
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive control
Adaptive control systems
Algorithms
Control systems
Controllers
Convergence
Cost function
Impedance matching
Linear systems
Matching
Optimal control
Optimization
Programmable control
Stochastic processes
Stochastic systems
Stochasticity
Vectors
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Summary:Optimal adaptive controller based on the ELS algorithm is established using the input matching technique. The control signal is reduced to a constant weighted sum of the measurable information-state vector components using a one-step-ahead quadratic cost function to govern the behavior of the stochastic linear systems. The control effort can be estimated globally. The algorithm also predicts the convergence rate. With no excitation condition, the closed-loop system is globally stable and the input converges to the one-step-ahead optimal input.
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ISSN:0018-9286
1558-2523
DOI:10.1109/9.855567