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Information Journal Paper

Title

Designing and simulating model predictive controller based on type-2 fuzzy system for a nonlinear boiler-turbine system

Pages

  240-250

Abstract

 In this paper, a novel Model predictive control method is presented for controlling a Boiler-turbine system as an uncertain nonlinear system. In the proposed method, Type-2 fuzzy system is used to cope with steady state error or bias appeared in the predictive control method due to the effects of model mismatch. For this purpose, using a piece-wise linear model of the system and considering the constraints in the system and the control signal, a predictive controller is designed to solve a constrained optimization problem. . In the presented control scheme, a type-2 fuzzy supervisor is used to adjust the reference input signal according to the system conditions. It has been shown that utilizing Type-2 fuzzy system in the predictive control method, instead of Type-1 fuzzy system, leads to satisfactory results. The proposed method is applied to the nonlinear model of the Boiler-turbine system and the simulation results show the effectiveness of this method compared with the existing fuzzy predictive control methods, especially for the conditions in which the model uncertainty is present.

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  • Cite

    APA: Copy

    AZIZI, M., & REZAIE, B.. (2018). Designing and simulating model predictive controller based on type-2 fuzzy system for a nonlinear boiler-turbine system. MODARES MECHANICAL ENGINEERING, 18(6 ), 240-250. SID. https://sid.ir/paper/178111/en

    Vancouver: Copy

    AZIZI M., REZAIE B.. Designing and simulating model predictive controller based on type-2 fuzzy system for a nonlinear boiler-turbine system. MODARES MECHANICAL ENGINEERING[Internet]. 2018;18(6 ):240-250. Available from: https://sid.ir/paper/178111/en

    IEEE: Copy

    M. AZIZI, and B. REZAIE, “Designing and simulating model predictive controller based on type-2 fuzzy system for a nonlinear boiler-turbine system,” MODARES MECHANICAL ENGINEERING, vol. 18, no. 6 , pp. 240–250, 2018, [Online]. Available: https://sid.ir/paper/178111/en

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