Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6952868 | Journal of the Franklin Institute | 2018 | 20 Pages |
Abstract
This paper proposes a multivariate extremum seeking with the Newton method (ES-NM) to improve the control performance for multivariable static and dynamic systems. The structure of the proposed ES-NM is designed to speed up the convergence of the scheme without increasing the oscillation. The influence of unknown Hessian matrix on the convergence speed existed in conventional methods is effectively eliminated in the proposed ES-NM approach. The stability analysis of the proposed ES-NM is given in detail for static and dynamic systems. Comparisons to the existing Gradient based extremum seeking control (ESC) and the Newton based ESC reveal that the proposed ES-NM has a higher probability of improving the convergence speed as well as reducing the chattering performance. Simulation results show advantages of the proposed ES-NM by comparing the multivariate Gradient based and Newton based ESC.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Chun Yin, Shanshan Wu, Shiwei Zhou, Jiuwen Cao, Xuegang Huang, Yuhua Cheng,