Adaptive fuzzy tracking control for vibration suppression of a cable-driven parallel hoisting robot

In practical engineering applications, most of the system parameters required for controlling cable-driven parallel hoisting robot (CDPHR) are unobtainable with precision. Additionally, when operating under various environmental conditions, the CDPHR is often disturbed by external unknown damping. These factors render the payload vibration suppression control during the motion of the CDPHR a challenging problem. Currently, there are few control methods that simultaneously consider both aforementioned factors, and the control effectiveness in practical applications is often unsatisfactory. To address the above issues, an adaptive fuzzy tracking control method is proposed in this paper, which comprises an adaptive controller and an improved fuzzy controller. In the design of the adaptive controller, by isolating unknown system parameters and elaborately designing parameter update law, the effectively estimation for changes in system parameters is achieved. This also helps the system in better adapting to external damping disturbances. Furthermore, an adaptive sine-following sparrow search algorithm (ASFSSA) is proposed to improve the fuzzy controller by optimizing its quantization and scale factors. The improved fuzzy controller is used to adjust the gain parameters of the adaptive controller online according to changes in the system state, thereby further enhancing the robustness of system and better suppressing external disturbances. The simulation and experimental results demonstrate that the higher positioning accuracy and faster payload vibration suppression can be achieved by the proposed control method compared to other existing control methods. Furthermore, the robustness and effectiveness are also experimentally validated.