Adaptive Fuzzy Sliding Mode Control for Coal Silo Cleaning Robots Simulation, and Performance Analysis

During coal mining and storage, significant accumulation of coal dust and chunks often occurs in coal silos, reducing storage capacity and posing safety hazards. The coal silo environment is characterized by confined spaces, complex obstacles, high dust concentration, and significant variations in temperature and humidity, making the cleaning task highly challenging. This necessitates the development of control strategies that are precise, robust, and capable of adapting to complex environments. This paper presents an Adaptive Fuzzy Sliding Mode Controller (AFSMC) that integrates the robustness of sliding mode control with the smoothness of fuzzy control and employs an adaptive mechanism to adjust control parameters in real time. Specifically, AFSMC increases the control gain when encountering significant resistance from coal chunks to ensure sufficient torque for cleaning, and decreases the gain under lighter loads to minimize energy consumption and reduce mechanical fatigue. Simulation results demonstrate that AFSMC achieves high-precision and energy-efficient trajectory tracking, effectively reduces chattering, and significantly enhances overall system performance. This research provides an efficient and robust control solution for coal silo cleaning robots, meeting the demands of dynamic and complex mining environments and advancing intelligent cleaning technology in the coal industry.