Title :
The application of improved genetic algorithm in nonlinear PID control
Author :
Shao, Max K -Y ; Li, Fei ; Jiang, B. -Y ; Zhang, H.-Y. ; Li, W.-C. ; Zhang, X. -G
Author_Institution :
Sch. of Electr. & Inf. Eng., Northeast Pet. Univ., Daqing, China
Abstract :
A method that integrates nonlinear PID control and genetic algorithm is introduced for the drawback of traditional PID control. It combines the global convergence of genetic algorithm and self-adaptive capacity of nonlinear PID and enhances the accuracy and robustness of the control. In the genetic operations, a crossover program related to the individual fitness is designed based on random non-uniform linear cross to prevent the loss of good genes after cross. A scheme that presents a crossover rate and mutation rate can adjust adaptively responds to the evolutionary process is provided, which ensures the global search capability during prophase and population diversity during later period. The scheme was applied to the control of one order time-delay system and simulation results show that the speed, stability and accuracy of the controlled system is improved.
Keywords :
genetic algorithms; nonlinear control systems; stability; three-term control; evolutionary process; genetic algorithm; global convergence; global search capability; nonlinear PID control; population diversity; self-adaptive capacity; stability; Accuracy; Evolutionary computation; Genetic algorithms; Genetics; Optimization; Petroleum; Robustness; PID control; adaptively adjust; genetic algorithm; nonlinear;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2011 9th World Congress on
Conference_Location :
Taipei
Print_ISBN :
978-1-61284-698-9
DOI :
10.1109/WCICA.2011.5970624