An Audio-Based Iterative Controller for Soft Landing of Electromechanical Relays

TL;DR

This paper introduces an innovative audio-based iterative control method for electromechanical relays, significantly reducing collision impacts during switching by combining flux-tracking, feedforward, and adaptive learning components.

Contribution

It presents a novel soft landing control strategy utilizing audio signals for iterative model adaptation, improving relay switching performance and longevity.

Findings

Effective reduction of switching collisions demonstrated

Adaptive control improves model accuracy over iterations

Experimental validation confirms robustness and efficiency

Abstract

Electromechanical relays and contactors suffer from strong collisions at the end of the switching operations. This causes several undesirable phenomena, such as clicking, mechanical wear and contact bounce. Thus, there is great interest in mitigating these switching impacts while keeping the advantageous features of these devices. This paper proposes a complete control strategy for soft landing. The control structure includes three main components. The first one is a real-time flux-tracking feedback controller, which presents several advantages over voltage or current control. The second one is a feedforward controller, which computes the flux reference signal based on a proposed dynamical model and the desired position trajectory for the switching operations. Lastly, the third control component is a learning-type run-to-run adaptation law that iteratively adapts the model parameters based on an audio signal. It exploits the repetitive nature of these devices in order to circumvent modeling discrepancies due to unit-to-unit variability or small changes between operations. The effectiveness of the proposed control is demonstrated through various experiments.