Optimization of the Linear Systems with Unknown Dynamics Using Intelligent Operations Research Techniques
published by Aِl-Baath University
in 2016
in Mathematics
and research's language is
العربية
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Abstract in English
This paper presents a method for finding online adaptive optimal
controllers for continuous-time linear systems without knowing the
system dynamical matrices. The proposed method employs one of
Intelligent Operations Research Techniques, this technique is the
adaptive dynamic programming, to iteratively solve the algebraic
Riccati equation using the online information of state and input,
without requiring the a priori knowledge of the system dynamics. In
addition, all iterations can be conducted by using repeatedly the
same state and input information on some fixed time intervals. A
practical online algorithm is developed in this paper, and is applied
to the controller design for a turbocharged diesel engine with
exhaust gas recirculation.
References used
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Bhasin, S., Sharma, N., Patre, P., & Dixon, W. E. (2011). Asymptotic tracking by a reinforcement learning-based adaptive critic controller. Journal of Control Theory and Applications, 9(3), 400–409