Robust and computationally efficient single-input fuzzy logic‑enhanced nonlinear PID control for a pneumatic servo system

Abstract

Precision and robustness are essential for any automation actuator. Due to the nonlinear characteristics of the pneumatic actuator, advanced nonlinear control algorithms provide exceptionally precise control but are sensitive to disturbances. Owing to this factor, an adaptive element is embedded into the control structure to obtain a robust strategy by integrating single input fuzzy logic (SIFL) with the nonlinear hyperbolic PID controller (T NPID). SIFL characterizes a variable rate in the function while reducing computational complexity against an equivalent classical fuzzy logic (FL) by up to 36.5%. The signed distance SIFL selection is also a novel structure that has never been applied in the pneumatics control field. The robustness of the controller is analysed via dynamic stiffness and validated by applying multiple load disturbances. The improvement gained for the T NPID+SIFL’s transient rise time and multi-step IAE index under no load disturbance is 71.381% and 68.854%, respectively, compared with a classical sliding mode controller (SMC). Under a maximum 9 kg load disturbance (limited within the scope of this research), the T NPID+SIFL’s IAE index performance obtained an improvement of 68.638%. When compared with a baseline nonlinear hyperbolic PID (NH PID) strategy under no load disturbance, the steady state error and overshoot also improved by 74.797% and 15.385%, respectively. The results show outstanding performance compared with a robust controller as well as a similar baseline nonlinear PID control. Asymptotic stability analysis, such as the asymptotic tracking region (ATR), will be able to consolidate the trajectory tracking performance together with the experimental validation of a smooth trajectory, simulating a real-time robotic actuator under movement control.