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A simulated annealing optimization algorithm based nonlinear model predictive control strategy with application

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Abstract

Batch reactors are widely used in the production of fine chemicals, polymers, pharmaceuticals and other specialty products. For certain exothermic reactions, the transient operation of the reactor with respect to small changes in critical parameters like coolant temperature and initial composition of the reactants can lead runaway condition of the reactor. In order to avoid the hazards associated with runaway situations, it is imperative to operate the reactor by means of an efficient controller. This work presents a nonlinear model predictive control (NMPC) strategy based on simulated annealing (SA) for the temperature control of a batch reactor involving a highly exothermic runaway reaction. The efficacy of the proposed strategy is studied through simulation for the temperature control of the reactor in which a highly parametric sensitive exothermic reaction of hydrolysis of acetic anhydride with sulfuric acid as catalyst and acetic acid as a solvent is carried out. The controller is found effective in averting the runaway behavior with the smooth and quick attainment of the desired operating condition. The results demonstrate the better performance of the SA based NMPC over the linear model predictive controller (LMPC).

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Acknowledgements

Financial assistance from DST, India through the grant SR/FST/College/2014 is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Chemical Engineering, B.V. Raju Institute of Technology, Narsapur, India

    M. Mallaiah & Ch. Venkateswarlu

  2. Petroleum and Chemical Engineering, Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    K. Rama Rao

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  1. M. Mallaiah
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  2. K. Rama Rao
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  3. Ch. Venkateswarlu
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Correspondence to Ch. Venkateswarlu.

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Mallaiah, M., Rama Rao, K. & Venkateswarlu, C. A simulated annealing optimization algorithm based nonlinear model predictive control strategy with application. Evolving Systems 12, 225–231 (2021). https://doi.org/10.1007/s12530-020-09354-1

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  • DOI: https://doi.org/10.1007/s12530-020-09354-1

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