基于改进蚁群算法的飞行仿真转台的控制优化

提出了一种用改进蚁群算法优化飞行仿真转台非线性PID控制参数的新策略,借助相遇搜索策略和信息素残留系数的自适应控制思想对基本蚁群算法进行了改进,设计了一种基于改进蚁群算法优化飞行仿真转台非线性PID(NLPID)控制参数的飞行仿真转台系统结构,在对非线性PID控制参数进行优化时采用了时间乘以误差绝对值积分最小性能指标,最后将用改进蚁群算法优化后的控制参数应用于某型高性能飞行仿真转台。实验表明,采用改进蚁群算法优化非线性PID控制参数的飞行仿真转台系统可从带噪声的输入信号中合理地提取出微分信号,并且对噪声具有很强的滤波作用,整个系统响应速度快,并具有较强的鲁棒性。

Study on the Improved ACA-based Parameters Optimization of NLPID Controller for Flight Simulator

A novel NLPID optimization strategy for flight simulator was proposed.In order to enhance the global convergence performance of ACA,the basic ACA was improved by using meeting search strategy and trail decay coefficient self-adaptive adjusting ideology.Furthermore,an improved ACA-based NLPID parameters optimization structure for flight simulator was designed.ITAE performance criteria was adopted in the improved ACA.Finally,the optimized parameters using improved ACA were applied to a high performance flight simulator.The experimental results demonstrate that the NLPID controller has strong robustness against noise.This proposed ACA-based HLPID parameters optimization strategy can also be used to develope other simulation servo system′controllers.