The Research Of Optimized PID Control Based On Self-adaptive Ant Colony Algorithm With Syncretic And Genetic Genes

Ant colony algorithm is a brand-new type of simulant evolution algorithm, which focuses on its solution to assemble optimized question and has been widely used to solve various problems, such as TSP, QAP. PID (Proportion-Integral-Differential) control has been widely used in industry control field. This paper is fully dependent on its advantages, such as the simple algorithm, well robustness, high reliability and good capability. Nowadays, as the demand for controlling process has been greater and greater, the research of intelligent PID control has become a key topic.The quality of PID control is fully dependent on the turning and optimization of PID parameter K_p, Td, Ti. The paper utilizes ant colony algorithm to optimize PID control parameter. However, in the Ant colony algorithm, there are some defects, such as slow convergence speed, easy to get stagnate, and low ability of full search. In this paper, a method of optimized PID control of self-adapted Ant colony algorithm based on genetic gene is proposed. The experimental results show that the algorithm has good performance in optimizing PID.The main works of this paper are as follows:1. The paper analyzes and discusses PID control and its algorithm, and then summarizes and studies PID control turning and optimization. Also this paper discusses the basic method of ant colony algorithm to optimize PID control parameter.2. The paper makes summarization in detail for the composing, theory capability and characteristic of ant colony algorithm. To solve the defects of ant algorithm, an optimized PID control parameter of self-adapted ant colony algorithm based on equilibrium of ant distribution are presented.3. Furthermore, optimized PID control parameter of self-adapted ant colony algorithm combined by genetic genes is addressed. In order to realize this extraordinary optimization, an optimized picture of ant colony algorithm PID control parameter is designed.The work of this paper shows that: the method, which optimizes PID control of self-adapted Ant colony algorithm based on genetic gene, overcomes the defect of Ant colony algorithm and can optimized PID control parameter well. The simulation results, which compare to the results of Z-N optimization and evolution of genetic algorithm optimization, shows that the dynamic access of system stepping reactionunitcand adjusting time ts decreasing greatly and also, dynamic and steady capacity are greatly improved.