一种改进的自适应Smith预估器

传统的Smith预估器是基于被控对象的精确数学模型而设计的,对于缺乏精确数学模型且参数时变的大时滞系统,常规的Smith预估控制规则就很难获得令人满意的控制效果。文章在一种增益自适应Smith预估补偿器的基础上,利用信号的相关性分析技术中的平均幅度差函数,实时调整预估器的滞后时间;仿真表明,该算法具有较好的性能,加强了Smith预估器抗干扰能力,改善了参数时变的大时滞系统的鲁棒性。

An improved self-adaptive Smith predictor

The traditional Smith predictor is based on the precise mathematical model of the controlled objects.For the system which can not be described by the precise mathematical model but has time-varying parameters and long dead-time,the normal Smith predictor is difficult to achieve good control effect.Based on a gain-adaptive Smith predictor,real-time estimation and regulation of the time delay is achieved by using the average magnitude difference function(AMDF) in the correlation analysis technique.Simulation results show that this algorithm has better performance,enhancing the Smith predictor's capacity of anti-jamming and improving robustness of the system with long dead-time and time-varying parameters.