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Stochastic state-feedback control using homotopy optimization and particle filtering

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Abstract

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.

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Funding

No funding agency for the research work carried out in this article.

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Authors and Affiliations

  1. Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Hyderabad, 502285, India

    Venkata Goutham Polisetty & Phanindra Jampana

  2. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, T6G 1H9, Canada

    Santhosh Kumar Varanasi

Authors
  1. Venkata Goutham Polisetty
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  2. Santhosh Kumar Varanasi
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  3. Phanindra Jampana
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Contributions

First Author (Mr. Venkata Goutham Polisetty) has written most of the paper, carried out most of the research work, obtained all the simulation results, their presentation and analysis. He has also written detailed responses to the reviewers with the required simulations. Second Author (Dr. Santhosh Kumar Varanasi) has assisted the First Author in the simulation work, has written some parts of the paper and also contributed to the development of part of the theory (i.e., sigmoid basis). Corresponding author (Dr. Phanindra Jampana) has provided the overall inputs for the theoretical development of the filtering and the control algorithms. He also oversaw the revision process and the preparation of the reviewer comments.

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Correspondence to Phanindra Jampana.

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Polisetty, V.G., Varanasi, S.K. & Jampana, P. Stochastic state-feedback control using homotopy optimization and particle filtering. Int. J. Dynam. Control 10, 942–955 (2022). https://doi.org/10.1007/s40435-021-00853-w

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  • DOI: https://doi.org/10.1007/s40435-021-00853-w

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