Enhancing Servo Performance of a Two-Degree-of-Freedom Rotary Table Using Intelligent Control Optimized by SSA–GA

Abstract

The two-degree-of-freedom rotation stage serves as a crucial component in ground unmanned platforms, and its servo performance is pivotal to the platform’s overall functionality. To enhance the servo performance of the two-degree-of-freedom rotation stage, we proposed a novel adaptive control approach: SSA–GA optimization of RBFNN integration into PID control. This method leverages the SSA–GA algorithm to optimize the parameters within the RBFNN, which is then seamlessly integrated into the PID control framework. This integration enables precise control of the two-degree-of-freedom rotation stage, overcoming the limitations of traditional PID controllers. By simulating various real-world situations such as step, noise, sinusoidal, transient excitation, impulse and modelling errors, it is demonstrated that the proposed control method achieves significant improvement in terms of control accuracy, fast response and robustness. It offers a more effective and reliable method for controlling the two-degree-of-freedom rotation stage, addressing the challenges posed by various interfering factors. Meanwhile, through comprehensive comparisons with various optimization algorithms, we have proven that SSA–GA has the shortest optimization time. Consequently, the proposed method exhibits excellent application potential and broad prospects for future applications.