Conflict-Averse Multi-Objective Extremum Seeking and Its Application in Wastewater Treatment Processes

作者：M. S. Chu, Xin Huo, Kemao Ma · 发表于：IEEE Transactions on Automation Science and Engineering · 年份：2025 · DOI：10.1109/tase.2025.3552046 · 被引用次数：2 · 研究领域：Extremum Seeking Control Systems

This paper addresses multi-objective optimization problems using conflict-averse multi-objective extremum seeking (CAMOES) for unknown static mapping. As for the traditional multi-objective extremum seeking (MOES) methods, the initial conditions affect the optimal solution, which may result in over-optimizing some objectives. To overcome this issue, by minimizing the average loss function with the 2-norm of the worst individual objective, conflict-averse gradient estimator is investigated to determine the weighting factors and regularization parameter adaptively, extenuating the adverse impact of the prior parameters and initial conditions on the performance of extremum seeking. To cope with the integral windup problem for constrained inputs, penalty-function anti-windup mechanism is explored with smoothing saturation function for multiple-input multiple-output (MIMO) extremum seeking. The stability of CAMOES is theoretically analyzed. Some bi-objective optimization problems are conducted, including a numerical example and a practical problem for wastewater treatment processes (WWTPs). The results demonstrate that the proposed CAMOES exhibits competitive performance. Note to Practitioners—The initial conditions may lead to different Pareto solutions, which brings adverse impact on the multi-objective optimization performance in WWTPs. How to mitigate the influence of the initial parameters on the optimization performance and deal with the changing operation condition is the k...