Tension–speed control for transformer insulation-layer winding based on Hamiltonian theory

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Authors: Kewei Sun, 范承恒, Jiazhong Xu, Lingqiang Meng, Yuteng Yue
Cited by: 0
References: 17

Abstract

During the winding process of transformer insulation layers, strong nonlinear coupling between tension and speed makes the system highly sensitive to external disturbances. This paper presents a tension–speed coordinated control strategy based on feedback dissipative Hamiltonian theory. A nonlinear dynamic model incorporating the unwind roller, rewind roller, and swing-arm mechanism is developed, and the total system energy is formulated through a Hamiltonian energy function. Using the energy shaping and dissipation assignment, an outer-loop feedback controller is designed to achieve stable decoupled control under multiple operating conditions. To further improve robustness and dynamic performance under uncertain disturbances, an inner-loop control algorithm combining a nonlinear disturbance observer and command-filtered backstepping control is introduced for real-time disturbance compensation. Simulations and physical winding experiments were conducted at a rated speed of 60 r/min for three reference tensions (20 N, 30 N, and 50 N) under ±5 r/min speed-step disturbances. Results show that, compared with conventional cascaded proportional–integral–derivative (PID) control, the proposed method reduces tension overshoot from 3.1 to 1.4 N, steady-state error from ±2.0 to ±0.5 N, and response time from 0.45 to 0.29 seconds, achieving about 35% improvement in dynamic performance. Further comparison with a nonlinear proportional–integral–derivative (NPID) controller demonstrates roughly a 50% reduction in overshoot and a 45% improvement in steady-state accuracy. Overall, the proposed Hamiltonian-based control approach provides high precision, strong robustness, and excellent real-time performance for industrial transformer insulation-layer winding systems.

Fields of Study & Subjects

Control and Stability of Dynamical Systems Control Systems in Engineering Adaptive Control of Nonlinear Systems

Publication details

Journal / source
Transactions of the Institute of Measurement and Control
Publication date
7 March 2026
Language
EN