Parameter Optimization for AP1000 Steam Generator Feedwater Control System Using Particle Swarm Optimization Algorithm

2016 ◽  
Author(s):  
Shifa Wu ◽  
Pengfei Wang ◽  
Jiashuang Wan ◽  
Xinyu Wei ◽  
Fuyu Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Water Level ◽  
Steam Generator ◽  
Parameter Optimization ◽  
Particle Swarm ◽  
Operating Conditions ◽  
Control Performance ◽  
Level Control ◽  
Swarm Optimization

The U-tube Steam Generator (UTSG) of AP1000 Nuclear Power Plant (NPP) is the crucial component transferring heat from the primary loop to the secondary loop to make steam. The UTSG of AP1000 NPP is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, it is difficult and challenging to well control the water level of AP1000 UTSG by tuning the PID controller parameter in a traditional way, especially when the system is undergoing a sharp transient. To achieve better control performance, the Particle Swarm Optimization (PSO) algorithm was applied for the parameter optimization of the AP1000 UTSG feedwater control system in this study. First, the mathematical model of AP1000 UTSG was established and the objective function was developed with the system constraints considered. Second, the simulation platform was built and then the simulation was conducted in MATLAB/Simulink environment. Finally, the optimized parameters were obtained and the feedwater control system with optimized parameters was simulated against that without optimized. The simulation results demonstrate that optimized parameters of AP1000 UTSG feedwater control system can significantly improve the water level control performance with smaller overshoot and faster response. Therefore, the PSO based optimization method can be applied to optimizing AP1000 UTSG feedwater control system parameters to provide much better control capabilities.

Parameter Optimization of Steam Generator Feedwater Controller Based on Particle Swarm Optimization

2013 ◽  
Vol 291-294 ◽  
pp. 2496-2499
Author(s):  
Rui Xiang ◽  
Rui Yu ◽  
Zhi Wu Ke ◽  
Ke Long Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Water Level ◽  
Steam Generator ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Step Response ◽  
Swarm Optimization ◽  
Response Characteristics ◽  
Water Lever

The U-tube steam generator(SG), as the joint of primary and secondary circuits, is one of the crucial components in a PWR plant. Because of the swell-and-shrink phenomena, it is very difficult to control the water level of the steam generator. Presently the three-element controller in cascade configuration with two PID controller is widely use. But the determination of the six optimal PID parameters of the cascade controller is a major problem. This paper studies the application of the particle swarm optimization(PSO) methods in determining the parameters of cascade controller of SG water lever. The SG is modeled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with conventional PID parameter, the proposed method is more efficient in improving the step response characteristics while controlling the water level of SG.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

A new control system design for a small hydro-power plant based on particle swarm optimization-fuzzy sliding mode controller with Kalman estimator

2011 ◽  
Vol 34 (4) ◽  
pp. 388-400 ◽  
Author(s):  
A Zargari ◽  
R Hooshmand ◽  
M Ataei
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Sliding Mode ◽  
Particle Swarm ◽  
Local Network ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Hydro Power ◽  
Fuzzy Sliding Mode ◽  
System Variables

One of the main problems in small hydro-power plants that are locally used is their frequency control system. In this paper, a suggested control system based on the fuzzy sliding mode controller is presented for controlling the network frequency. Also, the proposed control strategy is compared with a PI controller and conventional sliding mode controller. In order to regulate the membership functions of fuzzy system more accurately, the particle swarm optimization algorithm is also applied. Moreover, because of unavailability of the control system variables, an estimator is suggested for estimating and identifying the system variables. This estimator will reduce the costs of implementing the control method. The simulation results show the ability of controller system in controlling the local network frequency in the presence of load and parameter’s variations.

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