• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2595-2609
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• 2024

This paper introduces a base isolation system-tuned mass damper inerter (BIS-TMDI) hybrid system to the AP1000 nuclear power plant (NPP), which reduces seismic damage potential of the NPP structure. The effects of fluid-structure interaction (FSI) caused by the passive containment cooling system water storage tank (PCCWST) on NPP's seismic performance are investigated. The FSI of water tank theoretical model is considered based on the Housner's model, and a series of time history analyses are performed to prove the rationality of the proposed model. Three single-objective optimization strategies are employed to minimize the relative displacement variance and absolute acceleration variance of the upper structure, as well as the filtered energy index (FEI). Furthermore, a multi-objective optimization strategy considering all these three indexes is proposed to obtain optimal parameters of vibration control. The influence of vibration control strategies on the relative deformation and acceleration of the upper structure is explored with various water level ratios. The analytical results indicate that the proposed BIS-TMDI strategy has significantly reduced the NPP structure's seismic response. The effectiveness of the vibration control strategy is influenced by the water level ratio, emphasizing the significance of designing an appropriate water level ratio to reduce NPP structure's seismic response.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.