Work

Parameter Optimization of ADRC for Rolling-Mill Hydraulic Screw-Down Synchronization Based on a WMA–PSO Hybrid Algorithm

Year: 2026

Type: article

Abstract: Parameter tuning for Active Disturbance Rejection Control (ADRC) in rolling mill hydraulic synchronization systems is critical for enhancing strip quality. Conventional manual trial-and-error methods often yield suboptimal results. This paper proposes a hybrid algorithm, WMA-PSO, integrating the Humpback Whale Migration Algorithm (WMA) with Particle Swarm Optimization (PSO) through an adaptive fusion weight strategy. This approach effectively balances global exploration and local exploitation, improving optimization accuracy and efficiency. Evaluation on the CEC-2005 benchmark suite shows that WMA-PSO outperforms several state-of-the-art algorithms. Simulation experiments on ADRC tuning in a rolling mill system demonstrate that the WMA-PSO-optimized controller achieves the smallest synchronization error and superior overall control performance compared to other methods. The results validate WMA-PSO as an effective tool for automated parameter tuning in complex industrial control systems.

Source: Mathematics

DOI: 10.3390/math14050799

Authors: Yixuan Yang, Fei Zhang, Zhao Hong, Xuezhong Huang, Ye Du, Yanjiao Li

Institutions: University of Science and Technology Beijing, University of Leeds

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funders: University of Science and Technology Beijing, National Key Research and Development Program of China