A chattering-free sliding mode control strategy for modular high-temperature gas-cooled reactors

Wang, Guoxu; Wu, Jie; Zeng, Bifan; Xu, Zhibin; Ma, Xiaoqian

doi:10.1016/j.anucene.2019.07.003

Cited by 24 publications

(4 citation statements)

References 48 publications

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“…The major drawback of the SMC is the chattering issue, which degrades the control performance, reduces the life of the actuator, and may excite high-frequency unmodeled dynamics. For these reasons, substantial methods on chattering reduction have been developed in recent years, such as the boundary layer method [20][21][22], adaptive control [23,24], fuzzy logic control [25,26], high-order SMC (HOSMC) [27][28][29]. Among these methods, the HOSMC method is the most effective chattering suppression method by hiding discontinuous terms behind an integrator [30].…”

Section: Introductionmentioning

confidence: 99%

Station-Keeping Control of Autonomous and Remotely-Operated Vehicles for Free Floating Manipulation

Ding

Tang

Jiang

et al. 2021

JMSE

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This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) enhanced by adaptive tracking differentiator (ATD) and reduced-order extended state observer (RESO) is proposed. The ATD is used to obtain the smooth reference signal and its derivative. The RESO is used to estimate and compensate for the model uncertainties and external disturbances in real-time, which enhances the robustness of the controller. The modified AGSTA ensures the fast convergence of the system states and maintains them in a predefined neighborhood of origin without overestimating control gains. Besides, the proposed new variable gain strategy completely avoids the control gains vibrating near the set minimum value. Thanks to the RESO, the proposed controller is model-free and can be easily implemented in practice. The stability of the closed-loop system is analyzed based on Lyapunov’s direct method in the time domain. Finally, the proposed control scheme is applied to the station-keeping control of Haidou-1 ARV, and the simulation results confirm the superiority of the proposed control scheme over the original AGSTA.

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Section: Introductionmentioning

confidence: 99%

Station-Keeping Control of Autonomous and Remotely-Operated Vehicles for Free Floating Manipulation

Ding

Tang

Jiang

et al. 2021

JMSE

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“…The lumped parameter model is usually described by ODEs, which are mainly used to describe a simplified minimum dynamics model and facilitate the design of control systems. For example, [165] described the dynamic model of the lumped parameters of each modeling object of HTR-PM in a statespace manner to provide a basis for the subsequent analysis and synthesis of the control system [166], where [166] used the TS fuzzy technique to model the nonlinear dynamics of the HTGR system considering the uncertainty of the system. [167] established a dynamic model of 5MW Mi-HTR (microhigh-temperature GCR) by theoretical derivation, including the reactor model and the energy conversion system model, and linearized and Laplace transformed the model to obtain the transfer function model between different inputs and outputs.…”

Section: B Modelingmentioning

confidence: 99%

Small Modular Reactors: An Overview of Modeling, Control, Simulation, and Applications

Wang,

Chen,

Zhang

et al. 2024

IEEE Access

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A small modular reactor (SMR) is a nuclear reactor that is characterized by its smaller size and capacity when compared to traditional large-scale nuclear reactors. An SMR is often categorized as having an electrical output of less than 300MW and is built to be more mobile, safe, and extensible to deploy. It has been established that SMRs can provide economic and flexibility advantages in a variety of industries thanks to the development, study, and use of multiple types of SMRs in recent years. The goal of this paper is to present a comprehensive overview of several SMR types, including light water reactors (LWRs), liquid metal-cooled reactors (LMRs), molten salt reactors (MSRs), and gas-cooled reactors (GCRs). Each type of reactor will be reviewed in terms of its structural design, modeling control implementation, applications, and impacts concerning the power system.INDEX TERMS Digital simulation, mathematical modeling, power system control, reactor design, small modular reactors, nuclear power.

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“…Aiming at the power control problem of advanced boiling-water reactor, Huang et al [12] designed a multiple-input multiple-output fuzzy adaptive recursive sliding mode controller (FARSMC), which eliminates the chattering phenomenon of the sliding mode controller and realizes the parameter adaptation by using fuzzy logic. Hui and Yuan [13] designed a second-order sliding mode controller for reactor power based on state observer, and used neural network to approximate some state variables in the reactor model, which reduced the chattering effect of the controller; Wang et al [14] established the reactor model based on T-S fuzzy theory, and used the continuous switching function as the sliding mode function to reduce the chattering of the controller.…”

Section: Introductionmentioning

confidence: 99%

Nuclear power predictive sliding mode control based on state observer

Tan¹,

Zhou²

2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

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Nuclear reactor is the energy core of nuclear power plant. In order to ensure the efficient and stable operation of nuclear power plant and continuously output the thermal power generated by nuclear fission, it is necessary to control the power of reactor under operating conditions. The nonlinear mathematical model of nuclear reactor core power is established by perturbation method for point-reactor kinetics equation, and a reduced-order Luenberger state observer is designed to observe and track the state variables that cannot be measured directly in the model. On this basis, a sliding mode control algorithm based on model prediction is designed to realize the state feedback control of reactor power. Compared with the traditional PID control algorithm and verified by simulation with MATLAB/Simulink software. The simulation results show that in the up and down stage of load power, the speed fluctuation of control rod of sliding mode controller (0.5-mm/s) is higher than that of PID controller (0.07-mm/s), but in the steady-state conditions, the relative power tracking error of sliding mode controller (4×10-4) is less than that of PID controller (3×10-3). The predictive sliding mode controller designed in this paper has better comprehensive performance than PID controller.

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A chattering-free sliding mode control strategy for modular high-temperature gas-cooled reactors

Cited by 24 publications

References 48 publications

Station-Keeping Control of Autonomous and Remotely-Operated Vehicles for Free Floating Manipulation

Station-Keeping Control of Autonomous and Remotely-Operated Vehicles for Free Floating Manipulation

Small Modular Reactors: An Overview of Modeling, Control, Simulation, and Applications

Nuclear power predictive sliding mode control based on state observer

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