Optimization of surface texture for friction modeling and performance enhancement in continuous rotary electro-hydraulic servo motors using the GMS model

This study investigates the friction and leakage issues in continuous rotary electro-hydraulic servo motors under ultra-low-speed conditions. The focus is on optimizing surface texture to improve lubrication and reduce friction, using a generalized Maxwell-slip (GMS) friction model. Static and dynamic parameters of the GMS model were identified and corrected through fluid–structure interaction simulations. Surface texture optimization was achieved using hybrid particle swarm optimization (PSO) and sparrow search algorithms (SSAs). An APD–MPC controller with adaptive scheduling was developed to validate the performance enhancement achieved through the mechanics-based optimization. Experimental results demonstrate that this method can control angular displacement fluctuations within ±0.0003° at ultra-low speeds of 0.0005°/s. In 18 Hz sinusoidal response tests, phase difference and amplitude difference were reduced by 62.8% and 96.6%, respectively, compared with traditional proportional–integral–derivative (PID) control. Experimental verification shows tracking errors within 10% in the 12 Hz working frequency band. This mechanics-based optimization method, with validation through control experiments, offers an effective solution for enhancing low-speed stability in high-precision electro-hydraulic servo systems.