Temperature Control Optimization for Heat Pipe Based on Particle Swarm Optimization

2018 ◽  
Author(s):  
Xi Zhu ◽  
Zhengju Li ◽  
Jing Wang ◽  
Feng Yao ◽  
Chunlin Du
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Pipe ◽  
Temperature Control ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Control 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.

Variable Structure Control based of Particle Swarm Optimization for MCFC

2011 ◽  
Vol 347-353 ◽  
pp. 3223-3227
Author(s):  
Fan Yang ◽  
Hao Li
Keyword(s):  
Particle Swarm Optimization ◽  
Temperature Control ◽  
External Disturbance ◽  
Particle Swarm ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Molten Carbonate Fuel Cell ◽  
Molten Carbonate ◽  
Swarm Optimization ◽  
Structure Control

Variable structure control (VSC) has the ability of overcoming chattering and external disturbance. In this paper the temperature control based of Variable Structure Control is presented for the molten carbonate fuel cell (MCFC) which is a promising device for stationary power and heat supply. The parameters of VSC are obtained by Particle Swarm Optimization (PSO). Numerical results demonstrate the effectiveness and advantages of this approach. The simulation and the results showed that the VSC and the PSO receding optimization applied to the MCFC temperature control yielded good performance.

Energy Efficient Temperature Control with Particle Swarm Optimization for Smart Buildings

2013 ◽  
Vol 711 ◽  
pp. 518-522
Author(s):  
Jeong Hyuk Kim ◽  
Chang Jin Boo ◽  
Ho Chan Kim
Keyword(s):  
Particle Swarm Optimization ◽  
Temperature Control ◽  
Energy Efficient ◽  
Peak Power ◽  
Control Algorithm ◽  
Particle Swarm ◽  
Energy Costs ◽  
Swarm Optimization ◽  
Smart Buildings ◽  
Switching Method

In this paper, the energy efficient temperature control algorithm in smart buildings is proposed using particle swarm optimization (PSO). A control horizon switching method with PSO is used for optimal control, and the TOU tariff is included to calculate the energy costs. Simulation results show that the reductions of energy cost and peak power can be obtained using proposed algorithms.

Design of Temperature Controllor in Diamond Synthetic Chamber Based on Multi-Objective Particle Swarm Optimization

2014 ◽  
Vol 496-500 ◽  
pp. 1448-1451
Author(s):  
Hong Yan Hua ◽  
Cheng Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Nonlinear Programming ◽  
Strong Convergence ◽  
Control Problem ◽  
Temperature Control ◽  
Particle Swarm ◽  
Nonlinear Programming Problem ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Simulation Results

Temperature control problem is a typical multi-constraint/multi-objective nonlinear programming problem in diamond synthetic chamber and it cannot be solved by conventional methods. This paper proposed a constraint multi-objective particle swarm optimization (CMOPSO) algorithm to solve the problem. Simulation results show that the CMOPSO algorithm can be used effectively in diamond temperature control and it has strong convergence optimization abilities for all different parameters and constraint conditions.

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