A Novel Extremum Seeking Control to Enhance Convergence and Robustness in the Presence of Nonlinear Dynamic Sensors  

作　　者：LIU Hengchang TAN Ying OETOMO Denny 

机构地区：[1]School of Electrical,Mechanical and Infrastructure Engineering,The University of Melbourne,Parkville VIC 3010,Australia

出　　处：《Journal of Systems Science & Complexity》2024年第1期3-21,共19页系统科学与复杂性学报（英文版）

基　　金：supported by the Australian Research Council Discovery under Grant No.DP200102402.

摘　　要：This paper focuses on optimizing an unknown cost function through extremum seeking(ES)control in the presence of a slow nonlinear dynamic sensor responsible for measuring the cost.In contrast to traditional perturbation-based ES control,which often suffers from sluggish convergence,the proposed method eliminates the time-scale separation between sensor dynamics and ES control by using the relative degree of the nonlinear sensor system.To improve the convergence rate,the authors incorporate high-frequency dither signals and a differentiator.To enhance the robustness with the existence of rapid disturbances,an off-the-shelf linear high-gain differentiator is applied.The first result demonstrates that,for any desired convergence rate,with properly tuned parameters for the proposed ES algorithm,the input of the cost function can converge to an arbitrarily small neighborhood of the optimal solution,starting from any initial condition within any given compact set.Furthermore,the second result shows the robustness of the proposed ES control in the presence of sufficiently fast,zero-mean periodic disturbances.Simulation results substantiate these theoretical findings.

关 键 词：AVERAGING extremum seeking optimization singular perturbation time-scale separation 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TP212[自动化与计算机技术—控制科学与工程]