基于ekf的随机非线性系统动态设定点调整的概率解耦控制

Qichun Zhang, Liang Hu
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引用次数: 11

摘要

针对一类随机非线性系统,提出了一种基于估计的动态设定点调整解耦控制方法。回路控制层采用PID控制器设计,设计过程完成后参数固定,可以认为是一个既存的控制回路。而补偿器则采用扩展卡尔曼滤波器,基于系统的估计状态,采用设定点调整方法实现概率意义上的输出解耦。基于系统输出的互信息,可以对设定点调整补偿器的参数进行优化。利用所提出的控制方案,对闭环系统的跟踪误差在概率为1的情况下的稳定性进行了分析。为了说明所提出的控制方案的有效性,给出了一个数值算例,结果表明系统是稳定的,同时实现了概率解耦。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic Decoupling Control for Stochastic Non-Linear Systems Using EKF-Based Dynamic Set-Point Adjustment
In this paper, a novel decoupling control scheme is presented for a class of stochastic non-linear systems by estimation-based dynamic set-point adjustment. The loop control layer is designed using PID controller where the parameters are fixed once the design procedure is completed, which can be considered as an existing control loop. While the compensator is designed to achieve output decoupling in probability sense by a set-point adjustment approach based on the estimated states of the systems using extended Kalman filter. Based upon the mutual information of the system outputs, the parameters of the set-point adjustment compensator can be optimised. Using this presented control scheme, the analysis of stability is given where the tracking errors of the closed-loop systems are bounded in probability one. To illustrate the effectiveness of the presented control scheme, one numerical example is given and the results show that the systems are stable and the probabilistic decoupling is achieved simultaneously.
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