Parameter optimization of PID controller for boiler combustion system based on adaptive genetic algorithm

2012 ◽  
Author(s):  
Jia-tang Cheng ◽  
Li Ai ◽  
Wei Xiong
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Adaptive Genetic Algorithm ◽  
Combustion System

Optimal fuzzy PID controller design for an active magnetic bearing system based on adaptive genetic algorithms

2014 ◽  
Vol 24 (5) ◽  
Author(s):  
HUNG-CHENG CHEN
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Controller Design ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Adaptive Genetic Algorithm ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Pid Controller Design ◽  
Amb System

We propose an adaptive genetic algorithm (AGA) for the multi-objective optimisation design of a fuzzy PID controller and apply it to the control of an active magnetic bearing (AMB) system. Unlike PID controllers with fixed gains, a fuzzy PID controller is expressed in terms of fuzzy rules whose consequences employ analytical PID expressions. The PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than conventional ones. Moreover, it can be easily used to develop a precise and fast control algorithm in an optimal design. An adaptive genetic algorithm is proposed to design the fuzzy PID controller. The centres of the triangular membership functions and the PID gains for all fuzzy control rules are selected as parameters to be determined. We also present a dynamic model of an AMB system for axial motion. The simulation results of this AMB system show that a fuzzy PID controller designed using the proposed AGA has good performance.

Simulation of PID Control of Belt Conveyor System in Coal Mine by an Improved Adaptive Genetic Algorithm

2014 ◽  
Vol 614 ◽  
pp. 215-218 ◽  
Author(s):  
Lei Yu ◽  
Xu Long Zhang ◽  
Feng Wang
Keyword(s):  
Genetic Algorithm ◽  
Coal Mine ◽  
Pid Control ◽  
Pid Controller ◽  
Parameters Optimization ◽  
Step Response ◽  
Adaptive Genetic Algorithm ◽  
Belt Conveyor ◽  
Conveyor System ◽  
And Performance

In order to improve the problem of premature and performance of optimization, an improved adaptive genetic algorithm is proposed for parameters optimization of coal mine belt conveyor PID controller by applying the number of iterations to the crossover operation and mutation operation of genetic algorithm. The simulation shows that the step response of the improved algorithm is superior to the traditional adaptive genetic algorithm.

The Design of Expert PID Parameter Optimized by Genetic Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3091-3094
Author(s):  
Jia Tang Cheng ◽  
Wei Xiong ◽  
Li Ai
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Pid Controller ◽  
Dynamic Performance ◽  
Parameter Tuning ◽  
Expert Pid ◽  
Parameter Values ◽  
Better Than

Aiming at the problems Expert PID parameter tuning for time-consuming, and the results are not necessarily the best. In this paper, genetic algorithm is introduced to the parameter optimization, finally get a set of optimal PID parameter values. In comparison with simulated experiments, the results show that the performance of the Designed to optimize the performance of optimization expert PID controller is better than conventional controller, can achieve good dynamic performance.

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