Stability Optimization of an Oil Sampling Machine Control System Based on Improved Sparrow Search Algorithm PID

This paper presents an automatic oil sampling system designed for vertical cylindrical oil tanks on land, focusing primarily on the structural design and control optimization for oil level measurement and liquid sampling inside the tank. First, the key structure and control architecture of the automatic sampler are introduced, explaining the collaborative working principles of its components to ensure good stability in system structure and motion control. On this basis, an improved Sparrow Search Algorithm (CSSA) is proposed, which integrates the Coati Optimization Algorithm (COA) and the traditional Sparrow Search Algorithm (SSA). This algorithm is used to optimize the parameters of the Proportional–Integral–Derivative (PID) control system in the oil sampler, aiming to address issues such as response delay, large overshoot, and insufficient stability that commonly occur in traditional PID control under complex conditions. This method achieves consistent response behavior over time and adaptiveness in the control process by dynamically adjusting the PID parameters in real time. To verify the effectiveness of the proposed control strategy, system simulations were conducted in the MATLAB 2024B environment, and a physical experimental platform was built for testing. The simulation compares the CSSA-PID controller with traditional PID, COA-PID, and SSA-PID control methods. In addition, a load disturbance was introduced at 300 ms to perform anti-interference comparative simulations. The results show that under CSSA-PID control, the system response time was shortened by up to 112 ms, the convergence speed improved by 72.3%, the global optimization capability was significantly enhanced, and the anti-interference ability was stronger. In the actual tests, the average error was reduced by approximately 45.3%. These results indicate that CSSA-PID can significantly enhance the stability and response speed of the control system. The efficient control of the automatic oil sampler will greatly enhance the intelligence and efficiency of oil level detection in tanks and reduce labor costs, having significant implications for the development of the grain and oil storage industry.