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Minimum attention stochastic control with homotopy optimization

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Abstract

A method of designing control inputs for tracking problems when models considered in the form of stochastic differential equations is proposed. Using the ideas of control vector parameterization, the control input identification problem is formulated as a parameter identification problem, which is solved using homotopy optimization. To further obtain a control with the least number of switchings, i.e., minimum attention control, a sparse recovery framework is developed. The accuracy of the proposed methods is demonstrated with the help of a linear second-order system and a non-linear quadruple tank system.

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Notes

  1. In a more general case, there might be amplitude constraints on the states and inputs, which are not considered in the current work.

  2. Though the example 1 considers systems with noise in all the states, the same approach will work for systems with degenerate K i.e., where in noise appears only in some of the state equations as considered in [26].

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Authors and Affiliations

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

    Santhosh Kumar Varanasi & Phanindra Jampana

  2. Department of Mechanical and Aerospace Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, 502285, India

    C. P. Vyasarayani

Authors
  1. Santhosh Kumar Varanasi
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  2. Phanindra Jampana
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  3. C. P. Vyasarayani
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Correspondence to C. P. Vyasarayani.

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Varanasi, S.K., Jampana, P. & Vyasarayani, C.P. Minimum attention stochastic control with homotopy optimization. Int. J. Dynam. Control 9, 266–274 (2021). https://doi.org/10.1007/s40435-020-00639-6

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  • DOI: https://doi.org/10.1007/s40435-020-00639-6

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