Generalized Predictive PID Control for Main Steam Temperature Based on Improved PSO Algorithm | Zendy

Zhongda Tian | Zendy; Shujiang Li | Zendy; Yanhong Wang | Zendy

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Generalized Predictive PID Control for Main Steam Temperature Based on Improved PSO Algorithm

Author(s) -

Zhongda Tian,

Shujiang Li,

Yanhong Wang

Publication year - 2017

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2017.p0507

Subject(s) - control theory (sociology) , pid controller , particle swarm optimization , overshoot (microwave communication) , computer science , model predictive control , temperature control , controller (irrigation) , inertia , fuzzy control system , convergence (economics) , control system , fuzzy logic , control engineering , algorithm , engineering , control (management) , artificial intelligence , telecommunications , agronomy , physics , electrical engineering , classical mechanics , economic growth , economics , biology

The large inertia and long delay characteristics of main steam temperature control system in thermal power plants will reduce the system control performance. In order to improve the system control performance, a generalized predictive PID control for main steam temperature strategy based on improved particle swarm optimization algorithm is proposed. The performance index of incremental PID controller of main control loop and PD controller of auxiliary control loop based on generalized predictive control algorithm is established. An improved particle swarm optimization algorithm with better fitness and faster convergence speed is proposed for online parameters optimization of performance index. The optimal control value of PID controller and PD controller can be obtained. The simulation experiment compared with fuzzy PID and fuzzy neural network is carried out. Simulation results show that proposed control method has faster response speed, smaller overshoot and control error, better tracking performance, and reduces the lag effect of the control system.

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