4.5 Article

Multiobjective robust H2/H∞ fuzzy tracking control for thermal system of power plant

期刊

JOURNAL OF PROCESS CONTROL
卷 70, 期 -, 页码 47-64

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2018.08.004

关键词

LMI; H-2/H-infinity; Fuzzy tracking control; Multiobjective problem; Superheat temperature system; State observer

资金

  1. National Natural Fund of China [71471060]
  2. Coal Based Key Scientific and Technological Project of Shanxi Province, China [MD2014-03-06-02]
  3. Fundamental Research Funds for the Central Universities [9163117009]

向作者/读者索取更多资源

In this study, we introduce a multiobjective robust fuzzy H-2/H-infinity tracking control scheme for nonlinear dynamic superheat temperature system of an ultra-supercritical power plant to guarantee the optimal H-2 and H-infinity, reference tracking performance simultaneously. A Takagi-Sugeno fuzzy model is first employed to approximate the nonlinear dynamics of the ultra-supercritical superheat temperature system. Sub-sequently, the H-2/H-infinity tracking control design problem is formulated as a multiobjective problem to simultaneously minimize the H-2 control performance index and H-infinity control performance index for the fuzzy system. Then, an indirect method is proposed to solve this multiobjective problem for the multiobjective H-2/H-infinity fuzzy tracking control design. Next, a linear matrix inequality-based multiobjective evolution algorithm is developed based on a non-dominating sorting scheme to efficiently search the set of Pareto optimal solutions for this multiobjective problem, from which the engineers can select a set of design parameters according to the system performance preferences. In order to improve the applicability to engineering projects, the state observer and error integrator are adopted in the control strategy. Finally, a simulation example of an ultra-supercritical superheat temperature system is presented to illustrate the design procedure and to confirm the robust and optimal tracking performance of the proposed method. (C) 2018 Elsevier Ltd. All rights reserved.

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