Maobo Hu, Haoping Wang, Yang Tian, N. Christov, I. Simeonov
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引用次数: 4
Abstract
The paper deals with the optimization of nonlinear systems by using Extremum Seeking Control (ESC) without any prior knowledge of the system model. An Extend Kalman Filter based Extremum Seeking Control (EKF based ESC) is proposed, which can make the amplitude of perturbation signal variable and ensure convergence to zero, i.e. without steady-state oscillation. The proposed ESC algorithm makes also possible to obtain more accurate gradient estimate and more rapid ESC convergence. The proposed EKF based ESC algorithm is applied to a fifth-order model of anaerobic digestion process and its performances are compared with the performances of the classical ESC algorithm.
Key Words: ESC, EKF, steady state oscillation, anaerobic digestion processes
本文研究了在不知道系统模型先验知识的情况下，利用极值寻求控制(ESC)对非线性系统进行优化。提出了一种基于扩展卡尔曼滤波的极值寻求控制(EKF based ESC)，该控制可以使扰动信号的幅值可变，并保证收敛到零，即无稳态振荡。提出的ESC算法还可以获得更精确的梯度估计和更快的ESC收敛速度。将提出的基于EKF的ESC算法应用于厌氧消化过程的五阶模型，并与经典ESC算法的性能进行了比较。关键词:ESC, EKF，稳态振荡，厌氧消化过程
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