원문정보
초록
영어
This paper presents a method of optimized PID parameter self-adapted ant colony algorithm with aberrance gene, based on ant colony algorithm. This method overcomes genetic algorithm’s defects of repeated iteration, slower solving efficiency, ordinary ant colony algorithm’s defects of slow convergence speed, easy to get stagnate, and low ability of full search. For a given system, the results of simulation experiments which compare to the result of Z-N optimization and evolution of genetic algorithm optimization and evolution of ant colony system optimization, it has more excellent performance in finding best solution and convergence, the PID parameters also have optimality, system possesses dynamic controlling and performance. The experiments show that this method has its practical value on controlling other objection and process.
목차
1. Introduction
2. Ant Colony System and Ant Algorithms
2.1 Ant Colony System
2.2 Ant Algorithm
3. Optimization Design Based on Gene and Ant Colony Algorithm of Parameters of PID Controller
3.1 Classical PID Controller
3.2 Introduction to PID Parameter Optimization Based On Self-Adaptive and Ants Mix Algorithm
4. Procedure for PID Parameter Optimization Based On Hybrid Classified Adaptive Ants Algorithm
5. Simulator
6. Conclusions
References