Refining H∞ Controller Performance With Extremum Seeking Control for Improved Disturbance Attenuation


EROL B.

IEEE Access, vol.13, pp.125080-125089, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13
  • Publication Date: 2025
  • Doi Number: 10.1109/access.2025.3586136
  • Journal Name: IEEE Access
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.125080-125089
  • Keywords: Adaptive control, disturbance attenuation, extremum seeking control (ESC), real-time optimization, structured ℌ∞ control, sub-optimal convergence
  • Yıldız Technical University Affiliated: Yes

Abstract

Robust disturbance attenuation is critical in automotive, active suspension systems to ensure vehicle stability and passenger comfort. Traditional ℌ∞ control methods effectively minimize disturbances but often result in high-order controllers, which are challenging to implement practically due to complexity and reduced robustness to unmodeled dynamics. Although fixed-order structured controllers mitigate these implementation difficulties, they inherently suffer from a performance gap compared to their full-order counterparts. This paper presents a novel hybrid tuning strategy that combines structured ℌ∞ control with Extremum Seeking Control (ESC) to optimize disturbance attenuation in a quarter-car active suspension system, specifically targeting the ℌ∞ norm within a critical frequency band. Initially, a structured sub-optimal ℌ∞ controller is designed using conventional robust control methodologies. Subsequently, ESC is uniquely employed to iteratively fine-tune controller parameters, exploiting known disturbance characteristics without requiring explicit system modeling. The proposed ESC-based tuning significantly enhances the sub-optimal controller’s performance, narrowing the gap between structured and full-order optimal controllers. Stability of the closed-loop system is maintained throughout the tuning process by employing small perturbations, slow adaptation rates, and continuous evaluation of the ℌ∞ norm. Simulation results clearly demonstrate the effectiveness of the proposed method, highlighting its potential to improve practical disturbance attenuation and overall performance.