Extended state observer based fuzzy model predictive control for ultra-supercritical boiler-turbine unit

Zhang, Fan; Wu, Xiao; Shen, Jiong

doi:10.1016/j.applthermaleng.2017.01.111

Cited by 63 publications

(33 citation statements)

References 29 publications

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“…The reference tracking and the economic performance were both realized. To realize satisfying control performance for ultra-supercritical boiler, a fuzzy model was obtained for the fuzzy MPC, and a linear extended state observer was improved to estimate plant behavior variations and unknown disturbances [7]. A state-space model was linearized on-line to improve the computationally efficient in model predictive control, and the results were similar to the results obtained with nonlinear model [8].…”

Section: Introductionmentioning

confidence: 89%

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The Potential of Fractional Order Distributed MPC Applied to Steam/Water Loop in Large Scale Ships

et al. 2020

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The steam/water loop is a crucial part of a steam power plant. However, satisfying control performance is difficult to obtain due to the frequent disturbance and load fluctuation. A fractional order model predictive control was studied in this paper to improve the control performance of the steam/water loop. Firstly, the dynamic of the steam/water loop was introduced in large-scale ships. Then, the model predictive control with an extended prediction self adaptive controller framework was designed for the steam/water loop with a distributed scheme. Instead of an integer cost function, a fractional order cost function was applied in the model predictive control optimization step. The superiority of the fractional order model predictive control was validated with reference tracking and load fluctuation experiments.

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Section: Introductionmentioning

confidence: 89%

“…MPC has become the mostly applied control strategy in a wide variety of areas, including petroleum, refining and chemical industries [5]. Part of the work about the application of MPC to the boiler system is shown in [6][7][8]. In the cost function, an economic index was included [6].…”

Section: Introductionmentioning

confidence: 99%

The Potential of Fractional Order Distributed MPC Applied to Steam/Water Loop in Large Scale Ships

et al. 2020

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“…In [26], Liu et al firstly presented a model of a USC unit using a fuzzy neural network, the results showing that the model's built-in fuzzy neural network had satisfactory accuracy and performance. In [27], a fuzzy model of the USC unit was firstly developed, and then based on the model, an extended state observer-based model predictive control was proposed. In [28], an improved Takagi-Sugeno fuzzy framework was applied to the modeling of a 1000 MW USC unit, the parameters were identified by a k-means++ algorithm and an improved stochastic gradient algorithm.…”

Section: Introductionmentioning

confidence: 99%

Stacked Auto-Encoder Modeling of an Ultra-Supercritical Boiler-Turbine System

et al. 2019

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The ultra-supercritical (USC) coal-fired boiler-turbine unit has been widely used in modern power plants due to its high efficiency and low emissions. Since it is a typical multivariable system with large inertia, severe nonlinearity, and strong coupling, building an accurate model of the system using traditional identification methods are almost impossible. In this paper, a deep neural network framework using stacked auto-encoders (SAEs) is presented as an effective way to model the USC unit. In the training process of SAE, maximum correntropy is chosen as the loss function, since it can effectively alleviate the influence of the outliers existing in USC unit data. The SAE model is trained and validated using the real-time measurement data generated in the USC unit, and then compared with the traditional multilayer perceptron network. The results show that SAE has superiority both in forecasting the dynamic behavior as well as eliminating the influence of outliers. Therefore, it can be applicable for the simulation analysis of a 1000 MW USC unit.

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“…To solve the aforementioned problems, reference [17] proposed an adaptive state feedback to handle the unknown uncertainties of the boiler-turbine unit, where the input constraint is however neglected. Reference [18] developed an extended state observer-based fuzzy MPC to overcome the nonlinearity and disturbances simultaneously. However, its compensation action is directly added to the input side, resulting in the destruction of the input constraints and overall optimality.…”

Section: Introductionmentioning

confidence: 99%

A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control

et al. 2018

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The control of an ultra-supercritical (USC) boiler–turbine power plant is critical in maintaining the safety of the sustainable power grid. However, it is challenging due to the internal nonlinearity, hard manipulation constraints, and widespread uncertainties. To this end, a fuzzy extended state observer (FESO)-based stable fuzzy predictive control (SFPC) approach is developed in this paper. First, the control difficulties of the USC boiler–turbine unit are analyzed. Then, based on a Takagi–Sugeno (T–S) fuzzy model, a new FESO is developed for nonlinear systems to achieve a more precise observation performance. The gain of FESO is determined by solving a series of linear matrix inequalities, while guaranteeing the stability of FESO. Then, by combining the proposed FESO with the SFPC, an integrated FESO–SFPC algorithm is devised. The disturbance rejection ability of the FESO–SFPC algorithm is analyzed theoretically. Simulation results on a 1000 MW USC boiler–turbine power plant model further validate the effectiveness of the proposed method.

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Extended state observer based fuzzy model predictive control for ultra-supercritical boiler-turbine unit

Cited by 63 publications

References 29 publications

The Potential of Fractional Order Distributed MPC Applied to Steam/Water Loop in Large Scale Ships

The Potential of Fractional Order Distributed MPC Applied to Steam/Water Loop in Large Scale Ships

Stacked Auto-Encoder Modeling of an Ultra-Supercritical Boiler-Turbine System

A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control

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