Stochastic state-feedback control using homotopy optimization and particle filtering

Polisetty, Venkata Goutham and Varanasi, Santhosh Kumar and Jampana, Phanindra Varma (2022) Stochastic state-feedback control using homotopy optimization and particle filtering. International Journal of Dynamics and Control, 10 (3). pp. 942-955. ISSN 2195-268X

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In this paper, a method of designing control inputs for stochastic nonlinear processes under state-feedback is proposed. The objective is to determine a control input that minimizes the expected value of the integral of error between the set-point and the states. Since the states may not be measured, they are estimated using a particle filtering algorithm. The optimal control design is then reformulated as a parameter estimation problem using control vector parameterization where the inputs are considered as a nonlinear function of the error between the state estimates and the set-point. The parameters are then computed through a homotopy based optimization method. The control performance resulting from proposed homotopy based optimization method is compared with that of direct optimization and an existing nonlinear control method on a Solid Oxide Fuel Cell (SOFC) stack model. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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IITH Creators:
IITH CreatorsORCiD
Jampana, Phanindra Varma
Item Type: Article
Uncontrolled Keywords: Control vector parameterization; Homotopy optimization; Particle filtering; Stochastic dynamic systems
Subjects: Materials Engineering > Materials engineering
Chemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 27 Jun 2022 06:19
Last Modified: 30 Jun 2022 05:43
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