LQGI/LTR based robust control technique for a pressurized water nuclear power plant

Vajpayee, Vineet; Becerra, Victor M.; Bausch, Nils; Deng, Jiamei; Shimjith, S. R.; Arul, A. John

doi:10.1016/j.anucene.2020.108105

Cited by 18 publications

(11 citation statements)

References 52 publications

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“…To avoid duplication of work here, a brief summary of the pressurizer model is given. For a detailed description of the studied NPP model, various model equations, plant parameters, and steady-state values of different variables the readers are kindly referred to [24], [48].…”

Section: Pwr Nuclear Power Plantmentioning

confidence: 99%

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L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant

Vajpayee

Becerra

Bausch

et al. 2021

IEEE Trans. Nucl. Sci.

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This work proposes adaptive control-based design strategies to control a pressurized water (PWR) nuclear power plant (NPP). An L1-adaptive-based state feedback control technique is proposed using linear quadratic Gaussian control and projection-based adaptation laws. The control scheme possesses good robustness capabilities in handling disturbances and uncertainties. A Robust L1-adaptive control technique is also proposed by combining the L1-adaptive control with the loop transfer recovery (LTR) technology. The framework hence gives strengthened robust set-point tracking performance given the matched and unmatched uncertainties and disturbances. The NPP model employed in the current work is defined by five-inputs, fiveoutputs, and thirty-eight state variables. A linear model for controller design is obtained by linearizing the nonlinear NPP model at operating conditions. Various simulations are carried out on subsystems of the NPP to verify the effectiveness of the proposed scheme. Numerical and statistical measures are computed for quantitative analysis of the controllers' performance. Several classical control design techniques are also implemented, and their performance is compared with the proposed adaptive control techniques.

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Section: Pwr Nuclear Power Plantmentioning

confidence: 99%

“…where p p is pressurizer pressure and l w is pressurizer level. The rest of the variables are defined in [24], [48].…”

Section: A Pressurizer Modelmentioning

confidence: 99%

L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant

Vajpayee

Becerra

Bausch

et al. 2021

IEEE Trans. Nucl. Sci.

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“…To avoid duplication of published work, the PWR-type nuclear power plant model is presented here in brief. For a detailed description, the readers are advised to refer to [26,28,29]. The values of plant parameters, steady-state values, and their detailed definitions are given in [26,28,29].…”

Section: Mathematical Model Of a Pwr Nuclear Power Plantmentioning

confidence: 99%

“…For a detailed description, the readers are advised to refer to [26,28,29]. The values of plant parameters, steady-state values, and their detailed definitions are given in [26,28,29].…”

Section: Mathematical Model Of a Pwr Nuclear Power Plantmentioning

confidence: 99%

Analysis of Transient Interactions between a PWR Nuclear Power Plant and a Faulted Electricity Grid

2021

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This paper presents the transient stability analysis of a pressurised water-type nuclear power plant following faults and disturbances affecting the electricity grid to which it is connected. The modelled nuclear plant consists of various integrated subsystems, such as core neutronics and thermal-hydraulics, piping and plenum, pressuriser, steam generator, turbine, governor, and dynamics shaft, in addition to the turbine-speed controller. The nonlinear nuclear power plant model is linearised at the operating point to acquire a linear model for controller design. The turbine-speed control loop effectively enacts a closed-loop implementation of the nuclear power plant connected to the electric grid. The various transient stability enhancement components such as the power system stabiliser, static var compensator, and static synchronous compensator are employed to test performance during severe contingencies. The interaction between the nuclear power plant, electric grid, and protection system is studied under various scenarios such as single-phase fault, three-phase fault, and permanent load loss. The performance of the nonlinear plant is further observed during load-following operation. The dynamic behaviour of the overall system is analysed using simulations in the MATLAB/Simulink/Simscape environment.

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“…Moreover, the daily load cycle variations that are due to the load-following mode can significantly degrade plant performance. Conventional controllers such as proportional-integral and linearquadratic controllers are unable to control a plant effectively and robustly in an uncertain environment [1], [2]. Thus, it is necessary to improve the regulation and control strategies to strengthen the security, reliability, and operability of NPPs.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Model Predictive Control Using Feedback Linearization for a Pressurized Water Nuclear Power Plant

et al. 2022

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The present work aims to introduce a nonlinear control scheme that combines intelligent feedback linearization (FBL) and a model predictive control (MPC) for a pressurized water reactor (PWR). The nonlinear plant model that is considered in this study is described by the first-principles approach, and it consists of 38 state variables. First, system identification using a dynamic neural network (DNN) structure is performed to obtain a standard affine nonlinear system. The quasi-Newton algorithm is employed to find the best DNN model. Then, an FBL is formulated to address the nonlinearity of the DNN model. An MPC controller is developed based on the FBL system to improve the system performance. The designed controller is compared with a linear MPC controller that is based on state-space models to evaluate the performance of the proposed controller. The proposed approach improves the load-following operation and offers better disturbance rejection capability than the conventional MPC. In addition, numerical measures are employed to compare and analyse the performances of the two control strategies.

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LQGI/LTR based robust control technique for a pressurized water nuclear power plant

Cited by 18 publications

References 52 publications

L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant

L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant

Analysis of Transient Interactions between a PWR Nuclear Power Plant and a Faulted Electricity Grid

Nonlinear Model Predictive Control Using Feedback Linearization for a Pressurized Water Nuclear Power Plant

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