A Particle Swarm Optimization Approach for Optimal Design of PID Controller for Temperature Control in HVAC

2011 ◽  
Author(s):  
Zhang Jun ◽  
Zhang Kanyu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Design ◽  
Temperature Control ◽  
Pid Controller ◽  
Particle Swarm ◽  
Optimization Approach ◽  
Swarm Optimization

Application of Fuzzy Immune PID Controller Based on Particle Swarm Optimization in Power Plant Steam Temperature Control System

2014 ◽  
Vol 950 ◽  
pp. 257-262 ◽  
Author(s):  
Fei Hu ◽  
Wu Neng Zhou
Keyword(s):  
Particle Swarm Optimization ◽  
Power Plant ◽  
Temperature Control ◽  
Pid Control ◽  
Pid Controller ◽  
Particle Swarm ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Swarm Optimization ◽  
Adjustment Time

Power plant steam temperature control has characteristics of long delay and great inertia, a new method is proposed by analyzing above-mentioned problems and existing control methods on this paper. The method consists of an improved particle swarm optimization algorithm and a fuzzy immune PID controller. In addition, simulation results of PID, traditional fuzzy immune PID and fuzzy immune PID based on PSO are presented and compared. Fuzzy immune PID Control based on PSO has advantages of short adjustment time, quicker response time, better anti-interference ability and more stability. It can reduce the fluctuation of power plant steam temperature, and has better control performance and practical value.

Design and Experiment of Iterative Learning Controller Based on Particle Swarm Optimization Approach with New Bounded Constraints Technique

2013 ◽  
Vol 284-287 ◽  
pp. 2233-2237 ◽  
Author(s):  
Yi Cheng Huang ◽  
Yi Hao Li ◽  
Shu Ting Li
Keyword(s):  
Particle Swarm Optimization ◽  
Iterative Learning Control ◽  
Pid Controller ◽  
Particle Swarm ◽  
Iterative Learning ◽  
Optimization Approach ◽  
Proportional Integral Derivative ◽  
Swarm Optimization ◽  
Nonminimum Phase ◽  
Motion Profile

This paper utilizes the Improved Particle Swarm Optimization (IPSO) with bounded constraints technique for adjusting the gains of a Proportional-Integral-Derivative (PID) and Iterative Learning Control (ILC) controllers. This study compares the conventional ILC-PID controller with proposed IPSO-ILC-PID controller. A cycloid trajectory for mimicking the real industrial motion profile is applied. Two system plants with nonminimum phase are numerically simulated. Proposed IPSO with bounded constraints technique is evaluated on one axis of linear synchronous motor (LSM) with a PC-based real time controller. Simulations and experiment results show that the proposed controller can reduce the error significantly after two iterations.

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