Title :
Improved Chaos-GA-PID control in digital invert power supply
Author :
Bin, Duan ; Tongjing, Sun ; Zhenhua, Li ; Gaoqing, Mei ; Guangxian, Zhang
Author_Institution :
Dept. of Control Sci. & Eng., Univ. of Shandong, Jinan, China
Abstract :
For multi-parameter coupling nonlinear welding process, both chaos theory and genetic algorithm are used to achieve optimal matching of PID parameters, and the way to apply the algorithm for the welding machine is presented in this paper. First, requirements of invert welding machine control are analyzed. Encoding and decoding methods and fitness function are designed to form improved genetic algorithm. Then, chaos mechanism is researched to overcome randomness and avoid shortcomings of improved GA, such as local minimum value and prematurity. From the simulation experiments, it is shown that the improved chaos genetic algorithm is better than ANN-PID, fuzzy-PID and so on, has faster convergence speed and higher steady state accuracy, and can realize accurate regulation of welding current adaptively.
Keywords :
chaos; genetic algorithms; power supplies to apparatus; three-term control; welding; PID control; chaos theory; digital invert power supply; fitness function; genetic algorithm; invert welding machines; Chaos; Couplings; Decoding; Digital control; Encoding; Genetic algorithms; Machine control; Optimal matching; Power supplies; Welding; PID control; chaos theory; digital invert welding machine; genetic algorithm;
Conference_Titel :
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3863-1
Electronic_ISBN :
978-1-4244-3864-8
DOI :
10.1109/ICEMI.2009.5274595