Optimization of PID controller for water level control of the nuclear steam generator using PSO and GA

Author:

Safarzadeh Omid1ORCID,Tizdast Amir2

Affiliation:

1. Faculty of Engineering , Shahed University , Tehran , Iran

2. Faculty of Engineering , Shahid Beheshti University , Tehran , Iran

Abstract

Abstract The water level control system implicated in the nuclear steam generator has played an essential role in unexpected shutdowns of the power plant. According to reports, about 25% of the emergency power blackouts are caused by improper level control systems. The effectiveness of optimization methods in designing a controller is currently proved in different disciplines. The novelty of this paper is the proportional integral derivative (PID) controller tuning of nuclear steam generator by particle swarm optimization (PSO) and genetic algorithm (GA) for the lowest steady-state error, overshoot, undershoot, and settling time. Different types of the cost function are employed to obtain the controller gains. The integral of the absolute error (IAE), square error (ISE), time-weighted average error (ITAE), time-weighted square error (ITSE), and a weighted function based on overshoot, undershoot, and settling time are used. The gain scheduling of optimized PIDs is used to have an entire operating range control system. The desired load-following and stability of the optimized PID controller are investigated under both time and frequency domains using trajectory tracking, disturbance rejection, and Nichols chart criterion.

Publisher

Walter de Gruyter GmbH

Subject

Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics,Radiation

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. 3-Tank System Liquid Level Control Using Improved African Vulture Optimization Algorithm;2024 7th International Conference on Energy, Electrical and Power Engineering (CEEPE);2024-04-26

2. Optimization of PID Controller for Underwater Autonomous Vehicle Based on Particle Swarm Optimization Algorithm;2023 3rd International Conference on Electrical Engineering and Control Science (IC2ECS);2023-12-29

3. Tuning Method for Parameters in Fractional-Order PID Controllers Based on Neural Networks with Improved Borges Derivative;2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS);2023-05-12

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