The research of superheated steam temperature control based on generalized predictive control algorithm and adaptive forgetting factor

Jiang, Cheng; Qian, Hong; Pan, Yuekai; Chai, Tingting

doi:10.1002/acs.3066

Cited by 11 publications

(5 citation statements)

References 23 publications

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“…In order to soften the control effect, the output of the controlled object is not directly tracking the setting value, but tracks the reference trajectory. 43,44 The reference trajectory is determined by setting value y ref , output value y, and diffusion coefficient a(0 \ a \ 1).…”

Section: Input Channel Time-delay Compensationmentioning

confidence: 99%

Predictive control compensation for networked control system with time-delay

Tian

Wang

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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This study proposes a novel predictive control compensation method to deal with random time-delay in networked control system. Different from other compensation strategies, this study adopts different compensation strategies for input time-delay and output time-delay to improve the control effect. First, for the input channel time-delay, the corresponding buffer is set by the time-stamp in the packet. Combining the historical output value and the control variable, the fast implicit generalized predictive control algorithm is adopted to design the predictive controller to compensate for the input channel time-delay. Second, for the output channel time-delay, the controller cannot measure it. A control compensator is designed by adding a feedback loop. The output control variable of the predictive controller is adjusted by predicting the error between the actual control signal and the controller output at the historical sampling time, so as to compensate for the time-delay of the output channel. In addition, the stability of the proposed time-delay compensation method is analyzed. Finally, simulation and experimental results show that the proposed method has good control and compensation effect, and improves the output performance of the system. The networked control system with random time-delay is stable. Furthermore, the simulation results also show that this time-delay compensation method needs less computing time and is more suitable for the practical applications.

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Section: Input Channel Time-delay Compensationmentioning

confidence: 99%

Predictive control compensation for networked control system with time-delay

Tian

Wang

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…In addition, the input of the fuzzy control rules and the linguistic variables of the premise constitute the fuzzy input space, and the linguistic variables of the conclusion form the fuzzy output space. Therefore, the W, ΔW and modified value Δμ are segmented by a fuzzy method, and their fuzzy sets are obtained as follows (Jiang et al, 2020):…”

Section: Adaptive Adjustment Of Forgetting Factor Based On Fuzzy Algorithmmentioning

confidence: 99%

“…If the variable X ∈ R n×p , Y ∈ R n×q , and p is the number of independent variable, q is the number of dependent variable, n is the number of observed samples, the nonlinear mapping from the original input space {x j } p j 1 to the feature space H is recorded as Φ : x j ∈ R n → Φ(x j ) ∈ H (Jiang et al, 2020).…”

Section: Deviation Compensation Modelmentioning

confidence: 99%

Research on Adaptive Hybrid Energy Consumption Model Based on Data Driven under Variable Working Conditions

Su¹,

Zou

Jiang

et al. 2021

Front. Energy Res.

Self Cite

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As to the nonlinear and time-varying problems of the energy consumption model, this paper proposes an adaptive hybrid modeling method. Firstly, the recursive least squares algorithm with adaptive forgetting factor based on fuzzy algorithm and recursive least squares algorithm is used to identify the simplified mechanism energy consumption model, which solves the data saturation phenomenon and the weights of the “old and new” data during the online identification process and guarantees the adaptability of the mechanism model. Secondly, because there is a deviation between the identified model and the simplified mechanism energy consumption model, the deviation compensation model of mechanism model is established through kernel partial least squares algorithm and the model updating strategy with sliding window, which is used to update the deviation compensation model, and then the adaptive hybrid model is established by combining with the mechanism model identified online and updated deviation compensation model. Finally, the effectiveness, generalization and adaptability of the model are verified by the actual operating data of a single working condition and variable working conditions. And comparing with the mechanism model and the data model, The comparison results show that the adaptive hybrid model has higher calculation accuracy with adaptation.

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“…However, the obvious model error is generated when regarded the system frequency response model as the prediction model. Therefore, generalized predictive control with identification and adaptive mechanism reveals advantages (Cheng et al, 2019; Jiang et al, 2020; Kouvaritakis et al, 1992). The CARMAX model is close to the real model.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy decoupling predictive functional control for nonlinear hydro-turbine governing systems with mechanical time delay of the hydraulic servo system

Zhang

Wang

et al. 2022

Journal of Vibration and Control

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This study presents fuzzy decoupling predictive functional control for nonlinear hydro-turbine governing systems with time delay and strong coupling. Here, the Takagi–Sugeno fuzzy approach and fuzzy neural network decoupling algorithm are implemented in the pretreatment of a four-dimensional time delay hydro-turbine governing system model, aiming to solve the nonlinearity and separate coupling variables of the hydro-turbine governing system effectively. Then, a new fuzzy decoupling predictive functional control strategy proposed by combining the simplified hydro-turbine governing system model and predictive function control as well as the robustness and stability of the designed controller are verified by theoretical derivation. Numerical experiment demonstrates effectiveness and superiority of the proposed approach in comparison with fuzzy control under different operation conditions.

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The research of superheated steam temperature control based on generalized predictive control algorithm and adaptive forgetting factor

Cited by 11 publications

References 23 publications

Predictive control compensation for networked control system with time-delay

Predictive control compensation for networked control system with time-delay

Research on Adaptive Hybrid Energy Consumption Model Based on Data Driven under Variable Working Conditions

Fuzzy decoupling predictive functional control for nonlinear hydro-turbine governing systems with mechanical time delay of the hydraulic servo system

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