• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.851-859
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• 2021

Small PWR can be used for power generation and heating. Considering that small PWR has the characteristics of flexible operating conditions and complex operating environment, the controller designed based on single power level is difficult to achieve the ideal control of small PWR in the whole range of core power range. To solve this problem, a flexible switching controller based on fuzzy controller and LQG/LTR controller is designed. Firstly, a core fuzzy multi-model suitable for full power range is established. Then, T-S fuzzy rules are designed to realize the flexible switching between fuzzy controller and LQG/LTR controller. Finally, based on the core power feedback principle, the core flexible switching control system of small PWR is established and simulated. The results show that the flexible switching controller can effectively control the core power of small PWR and the control effect has the advantages of both fuzzy controller and LQG/LTR controller.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.4
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• pp.415-424
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• 2002

In this paper, a robust fuzzy precompensated PID controller using immune algorithm for load frequency control of 2-area power system is proposed. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic based precompensation approach for PID controller. This scheme is easily implemented by adding a fuzzy precompensator to an existing PID controller. We optimize the fuzzy precompensator with an immune algorithm for complementing the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and fuzzy rules. Simulation results show that the proposed robust load frequency controller can achieve good performance even in the presence of generation rate constraints.

• Journal of Drive and Control
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• v.15 no.1
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• pp.28-37
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• 2018

When the wind speed rises above the rated wind speed, the produced power of the wind turbines exceeds the rated power. Even more, the excessive power results in the undesirable mechanical load and fatigue. A solution to this problem is pitch control of the wind turbines. This paper presents a systematic design method of a collective pitch controller for the wind turbines using a discrete fuzzy Proportional-Integral (PI) controller. Unlike conventional PI controllers, the fuzzy PI controller has variable gains according to its input variables. Generally, tuning the parameters of fuzzy PI controller is complex due to the presence of too many parameters strongly coupled. In this paper, a systematic method for the fuzzy PI controller is presented. First, we show the fact that the fuzzy PI controller is a superset of the PI controller in the discrete-time domain and the initial parameters of the fuzzy PI controller is selected by using this relationship. Second, for simplicity of the design, we use only four rules to construct nonlinear fuzzy control surface. The tuning parameters of the proposed fuzzy PI controller are also obtained by the aforementioned relationship between the PI controller and the fuzzy PI controller. As a result, unlike the PI controller, the proposed fuzzy PI controller has variable gains which allow the pitch control system to operate in broader operating regions. The effectiveness of the proposed controller is verified with computer simulations using FAST, a NREL's primary computer-aided engineering tool for horizontal axis wind turbines.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1054-1057
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• 1993

A direct method of fuzzy inference and a fuzzy algorithm with learning function are applied to the steam generator level control of nuclear power plant. The fuzzy controller by use of direct inference can control the steam generator in the entire range of power level. There is a little long response time of fuzzy direct inference controller at low power level. The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0%∼30% of full power). Response time of steam generator level control at low power level with this rule base is shown generator level control at low power level with this rule base is shown to be shorter than that of fuzzy controller with direct inference.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.5
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• pp.484-493
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• 2011

The MPPT algorithm using neuro-fuzzy controller is proposed to improve the performance of fuzzy controller in this paper. The width of membership function and fuzzy rule have an effect on the performance of fuzzy controller. The neuro-fuzzy controller has the response characteristic which is superior to the existing fuzzy controller, because of using the optimal width of the fuzzy membership function through the neural learning. The superior control characteristic of a proposed algorithm is confirmed through simulation and experiment results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.62-69
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• 2000

In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PID control and a fuzzy precompensated PID control in dynamic responses about the load disturbances of power system and is convinced robustness reliableness in view of structure.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.699-703
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• 1991

A magnetic levitation system with hybrid magnets, which is composed of permanent magnets and electromagnets, consumes less power than the conventional attraction type system. In this paper, we propose PID controller and PID-Fuzzy controller for hybrid magnet. We first present "constant gap" control technology with PID controller. Secondly, "zero power" control technology with PID-Fuzzy hybrid controller is presented.roller is presented.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.97-106
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• 1999

This paper proposes the structure and the algorithm of the Fuzzy-Neural Controller(FNNC) which is able to adapt itself to unknown plant and the change of circumstances at the Fuzzy Logic Controller(FLC) with the Neural Network. This Learning Fuzzy Logic Controller is made up of Fuzzy Logic controller in charge of a main role and Neural Network of an adaptation in variable circumstances. This construct optimal fuzzy controller applied to the 2-area load frequency control of power system, and then it would examine fitness about parameter variation of plant or variation of circumstances. And it proposes the optimal Scale factor method wsint three preformance functions( E, , U) of system dynamics of load frequency control with error back-propagation learning algorithm. Applying the controller to the model of load frequency control, it is shown that the FNNC method has better rapidity for load disturbance, reduces load frequency maximum deviation and tie line power flow deviation and minimizes reaching and settling time compared to the Optimal Fuzzy Logic Controller(OFLC) and the Optimal Control for optimzation of performance index in past control techniques.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1978-1987
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• 2014

Power requirement to the induction heating system varies during the heating process. A closed loop control is required to have a smooth control over the power. In this work, a constant frequency pulse density modulation based power tracking control scheme for domestic induction heating system is developed using the Fuzzy Logic Controller. In the conventional power modulation schemes, the switching losses increase with the change in the load. The proposed pulse density modulation scheme maintains minimum switching losses for the entire load range. This scheme is implemented for the class-D series resonant inverter system. Fuzzy logic controller based power tracking control scheme is developed for domestic induction heating power supply for various power settings. The open loop and closed loop simulation studies are done using the MATLAB/Simulink simulation tool. The control logic is implemented in hardware using the PIC16F877A microcontroller. Fuzzy controller tracks the set power by changing the pulse density of the gate pulses applied to the inverter. The results obtained are used to know the effectiveness of the fuzzy logic controller to achieve the set power.