基于蚁群算法的PID参数优化

针对传统的PID控制器参数多采用试验加试凑的方式由人工进行优化,提出了一种新型的基于蚁群算法的PID参数优化策略.蚁群算法是近几年优化领域中新出现的一种仿生进化算法,该算法采用分布式并行计算机制.在简要介绍蚁群算法基本思想的基础上,推导了蚁群算法PID参数优化方法,并给出了新算法的具体实现步骤,最后将该优化方案应用于某型高精度飞行仿真伺服系统.仿真应用研究表明,该PID参数优化策略具有很强的灵活性、适应性和鲁棒性,进而验证了该方案的可行性和有效性.

Research and realization on parameters optimization of PID controller based on ant colony algorithm

In light of traditional PID controller parameters optimization with manual cut-and-try method, a novel kind of PID parameters optimization strategy based on ACA(Ant Colony Algorithm) was proposed. ACA is a new category of bionic algorithm for optimization problems. Parallel computation mechanism is adopted in this algorithm. On the basis of brief introduction of ACA, a method for setting PID controller parameters using ACA was derived. A detailed realizing process of the new algorithm was also presented. In the end, this new PID parameters optimization scheme was applied to some high precision flight simulation servo system. The simulation results show that the ACA based PID parameters optimization has excellent flexibility, adaptability and robustness. And the feasibility and effectiveness of this scheme is further verified.