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Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant

Puchalski B., Duzinkiewicz K., Rutkowski T.

Archives of Control Sciences

2015

Vol. 25, no. 4

429--444

In the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR) working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller which is designed for nominal power level of the nuclear reactor operates insufficiently well in wide range of operational conditions, especially at the low thermal power level. Thus the steam generator is often controlled manually by operators. Incorrect water level in the steam generator may lead to accidental shutdown of the nuclear reactor and consequently financial losses. In the paper a comparison of proposed multi region fuzzy logic controller and traditional PID controllers designed only for nominal condition is presented. The gains of the local PID controllers have been derived by solving appropriate optimization tasks with the cost function in a form of integrated squared error (ISE) criterion. In both cases, a model of steam generator which is readily available in literature was used for control algorithms synthesis purposes. The proposed multi-region fuzzy logic controller and traditional PID controller were subjected to broad-based simulation tests in rapid prototyping software - Matlab/Simulink. These tests proved the advantage of multi-region fuzzy logic controller with local PID controllers over its traditional counterpart.

Adaptive neurofuzzy predictive control of nuclear steam generators

Ahmad Z.

Nukleonika

2013

Vol. 58, No. 2

301--306

The main emphasis of this paper is the application of adaptive neurofuzzy model-based predictive control, to regulate the water level in the U-tube steam generating (UTSG) unit used for electricity generation. A nonlinear predictive controller is designed on the basis of a Takagi-Sugeno fuzzy model with B-spline membership function. By on-line adaptation of the neurofuzzy model, improvement of the control performance can be achieved with the time-variant process behaviour. For this purpose, a normalized least-square algorithm is utilized which exploits the local linearity of Takagi-Sugeno fuzzy models. An optimization approach with a quadratic programing technique is used to calculate predictions of the future control actions. The effectiveness and real-world applicability of the proposed approach are demonstrated by computer simulation. The control experiments were successfully conducted for this nonlinear process with satisfactory results and performances.