L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant
| Autor: | S. R. Shimjith, A. John Arul, Victor M. Becerra, Nils Bausch, Jiamei Deng, Vineet Vajpayee |
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| Rok vydání: | 2021 |
| Předmět: |
Nuclear and High Energy Physics
Projection (relational algebra) Adaptive control Nuclear Energy and Engineering Computer science Control theory Robustness (computer science) Control system Electrical and Electronic Engineering Robust control Type (model theory) Linear-quadratic-Gaussian control Optimal control |
| Zdroj: | IEEE Transactions on Nuclear Science. 68:1381-1398 |
| ISSN: | 1558-1578 0018-9499 |
| DOI: | 10.1109/tns.2021.3090526 |
| Popis: | This work proposes adaptive control-based design strategies to control a pressurized water reactor (PWR) nuclear power plant (NPP). An ${L_{1}}$ -adaptive-based state-feedback control technique is proposed using the linear quadratic Gaussian control and projection-based adaptation laws. The control scheme possesses good robustness capabilities in handling disturbances and uncertainties. A robust ${L_{1}}$ -adaptive control technique is also proposed by combining the ${L_{1}}$ -adaptive control with the loop transfer recovery (LTR) technology. The framework hence gives the strengthened robust set-point tracking performance given the matched and unmatched uncertainties and disturbances. The NPP model employed in this article is defined by five inputs, five outputs, and 38 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. |
| Databáze: | OpenAIRE |
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