Application of model free active disturbance rejection controller in nuclear reactor power control

Sun, Aodi; Pu, Songmao; He, Zhengxi; Xiao, Kai; Sun, Peiwei; Wang, Pengfei; Wei, Xinyu

doi:10.1016/j.pnucene.2021.103907

Cited by 21 publications

(4 citation statements)

References 8 publications

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“…This formulation of mixed-integer linear programming was used for NEPP analysis and optimization because it offered great flexibility in solving a variety of issues. integrating a model-free active disruptive control method for contrasting the controller's results with the conventional PID with reactive change and an extensive variety of power modifications in NEPP has been proposed as a solution to the issues that have emerged as a result of xenon fluctuations in the NE reactor core and the ranging reactivity in the core [14,26]. The PSO-PID controller offered greater robustness than the GM-PID controller when incorporated into the NPK model of the NE reactor for LF operations of PWR [27].…”

Section: Plos Onementioning

confidence: 99%

Optimal controller design for reactor core power stabilization in a pressurized water reactor: Applications of gold rush algorithm

Abdelfattah,

Esmail,

kotb

et al. 2024

PLoS ONE

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Nuclear energy (NE) is seen as a reliable choice for ensuring the security of the world’s energy supply, and it has only lately begun to be advocated as a strategy for reducing climate change in order to meet low-carbon energy transition goals. To achieve flexible operation across a wide operating range when it participates in peak regulation in the power systems, the pressurised water reactor (PWR) NE systems must overcome the nonlinearity problem induced by the substantial variation. In light of this viewpoint, the objective of this work is to evaluate the reactor core (main component) of the NE system via different recent optimization techniques. The PWR, which is the most common form, is the reactor under investigation. For controlling the movement of control rods that correspond with reactivity for power regulation the PWR, PID controller is employed. This study presents a dynamic model of the PWR, which includes the reactor core, the upper and lower plenums, and the piping that connects the reactor core to the steam alternator is analyzed and investigated. The PWR dynamic model is controlled by a PID controller optimized by the gold rush optimizer (GRO) built on the integration of the time-weighted square error performance indicator. Additionally, to exhibit the efficacy of the presented GRO, the dragonfly approach, Arithmetic algorithm, and planet optimization algorithm are used to adjust the PID controller parameters. Furthermore, a comparison among the optimized PID gains with the applied algorithms shows great accuracy, efficacy, and effectiveness of the proposed GRO. MATLAB\ Simulink program is used to model and simulate the system components and the applied algorithms. The simulation findings demonstrate that the suggested optimized PID control strategy has superior efficiency and resilience in terms of less overshoot and settling time.

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Section: Plos Onementioning

confidence: 99%

Optimal controller design for reactor core power stabilization in a pressurized water reactor: Applications of gold rush algorithm

Abdelfattah,

Esmail,

kotb

et al. 2024

PLoS ONE

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“…For the choice of control scheme, we have found some novel control schemes that may be suitable for this platform, including: Adaptive control, active disturbance rejection control, etc., [25], [26], and [27]. However, since the nuclear power control system is particularly important for the consideration of safety, the above new control algorithms are still in the theoretical research stage in our new reactor, and there are no practical engineering application cases of advanced control algorithms in previous nuclear power control systems.…”

Section: B the Control System Modelmentioning

confidence: 99%

Development of a Simulation and Control Platform for the China ADS Based on a Thermal Coupling Method

Zhang,

Shi,

et al. 2023

IEEE Access

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Accelerator driven subcritical reactors have attracted much attention in recent years for their ability to generate energy and transform radioactive waste in a cleaner and safer manner. As an important part of accelerator driven subcritical system (ADS), control system is directly related to the stable and safe operation of the system. Therefore, it is necessary to build a high-precision control system simulation platform that is easy to design and verify. In this paper, a simulation platform coupling Simulink and Locust is developed for the control system design of ADS in China. Based on an explicit thermal coupling strategy (TCS) of interface heat flux and wall temperature, the entire closed-loop system model is established. The simulation platform is divided into two parts according to the coolant type: the first part with lead bismuth eutectic is composed of the shell side of the interface heat exchanger (IHX), reactor, and main pump; the second part with water include the tube side of IHX, air cooler, feedwater pump, and flow network. To verify the effectiveness of the TCS method, the thermohydraulics parameters of once-through steam generator (OTSG) calculated by the coupled model were compared with those calculated by single Locust model under steady and transient conditions.The results show that the two models have good consistency. The coupled platform is able to successfully simulate dynamic processes under different conditions. In addition, simulation verification is carried out under the step change of 10% FP to study its control characteristics. The results show that the control effect of the coupled platform is slightly better than that of single Locust.The control system has a good ability to adjust the ADS system, and extends the functions of traditional Locust without modifying the Locust source code. While ensuring the accuracy of the model, it increases the flexibility of modeling and improves the modeling efficiency, which can provide an important reference for further engineering applications.

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“…Over time, the ADRC controller having an n-order design has been used for n-state systems (for n ≥ 1) [10][11][12]. The importance of ADRC design has been highlighted in scenarios involving practical applications and areas of academic research [13][14][15][16][17]. Several industrial applications, such as nuclear reactors, thermal power plants, medical practice, speed control processes, uncertain robotic systems, and teleoperation applications, were successfully controlled by the ADRC.…”

Section: Introductionmentioning

confidence: 99%

Predictive Extended State Observer-Based Active Disturbance Rejection Control for Systems with Time Delay

Nahri

Wyk

2023

Machines

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The latest research on disturbance rejection mechanisms has shown active disturbance rejection control (ADRC) to be an effective controller for uncertainties and nonlinear dynamics em-bedded in systems to be controlled. The significance of the ADRC controller is its model-free nature, as it requires minimal knowledge of the system model. In addition, it can actively estimate and compensate for the impact of internal and external disturbances present, with the aid of its crucial subsystem called the extended state observer (ESO). However, ADRC controller design becomes more challenging owing to different system disturbances, such as output disturbances, measure-ment noise, and varying time-delays persistent in the system’s communication channels. Most dis-turbance rejection techniques aim to reduce internal perturbations and external disturbances (input and output disturbance). However, output disturbance rejection with measurement noise under time-delay control is still a challenging problem. This paper presents a novel predictive ESO-based ADRC controller for time-delay systems by employing predictive methods to compensate for the disturbances originating from time delay. The prediction mechanism of the novel (proposed) con-troller design is greatly attributed to the extended state predictor observer (ESPO) integrated with the delay-based ADRC inside the proposed controller method. Thus, the proposed controller can predict the unknown system dynamics generated during the delay and compensate for these dy-namics via disturbance rejection under time-delay control. This approach uses the optimization mechanism to determine controller parameters, where the genetic algorithm (GA) is employed with the integral of time-weighted absolute error (ITAE) as the fitness function. The proposed controller is validated by controlling second-order systems with time delay. Type 0, Type 1, and Type 2 sys-tems are considered as the controlled plants, with disturbances (unknown dynamics due to delay and external disturbance), along with measurement noise present. The proposed controller method is compared with state-of-the-art methods, such as the modified time-delay-based ADRC method and the ESPO-based controller method. The findings indicate that the method proposed in this pa-per outperforms its existing competitors by compensating for the dynamics during the time delay and shows robust behaviour, improved disturbance rejection, and a fair extent of resilience to noise.

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Application of model free active disturbance rejection controller in nuclear reactor power control

Cited by 21 publications

References 8 publications

Optimal controller design for reactor core power stabilization in a pressurized water reactor: Applications of gold rush algorithm

Optimal controller design for reactor core power stabilization in a pressurized water reactor: Applications of gold rush algorithm

Development of a Simulation and Control Platform for the China ADS Based on a Thermal Coupling Method

Predictive Extended State Observer-Based Active Disturbance Rejection Control for Systems with Time Delay

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