PID controller parameters tuning of main steam temperature based on chaotic particle swarm optimization

The main steam temperature of thermal power units is an important control parameter to the safety and economic operation of the thermal power plant, which requires its long-term deviation to remain within ±5°C. In this paper, the PID control parameters are optimized through chaotic particle swarm optimization (CPSO). Adopting the Chaotic Ideology-logistic map to code the particles, the initial population has a good randomicity and ergodicity. Introducing the average optimal solution during the algorithm optimization process, the particles consult the search experience of the individual particle and the population to update the next generation, so that it can optimize the PID controller effectively and comprehensively. Meanwhile, the model of the main steam temperature is simulated in MATLAB respectively with Z-N tuning, genetic algorithm (GA) and chaotic particle swarm optimization (CPSO). The simulation result shows that because of the PID controller based on CPSO, the system responds fast and has a small overshoot. The system has a good control effect.