Neuromorphic Control of DC Motors With Static Friction-Dominated Dynamics

Friction is one of the main challenges in the control of electromechanical systems, as it appears in most mechanisms and severely degrades motion accuracy and efficiency. This Brief investigates a neuromorphic control (NC) strategy to address static friction in direct current (DC) motors operating near the dead zone. The proposed approach introduces a neuron-like modulator that encodes the output of a conventional controller into pulse trains, enabling the system to overcome the friction-induced dead zone while preserving the linear transient dynamics imposed by the main controller. The contributions of this work are threefold: 1) a theoretical analysis of the influence of neuron parameters on static-friction compensation and on the dynamic behavior of velocity and position responses; 2) the formulation of simple tuning rules for the two independent parameters of the strategy, facilitating practical implementation; and 3) experimental validation and comparison with conventional friction-compensation methods on a low-cost autonomous mobile robot, demonstrating a superior tradeoff between motion precision and energy efficiency, particularly at very low setpoints. These results confirm that the proposed approach is an effective, practical solution for friction-dominated systems, particularly suitable for energy-constrained robotic applications.