Design of a Hierarchical Control Architecture for Fully-Driven Multi-Fingered Dexterous Hand

Multi-fingered dexterous hands provide superior dexterity in complex manipulation tasks due to their high degrees of freedom (DOFs) and biomimetic structures. Inspired by the anatomical structure of human tendons and muscles, numerous robotic hands powered by pneumatic artificial muscles (PAMs) have been created to replicate the compliant and adaptable features of biological hands. Nonetheless, PAMs have inherent nonlinear and hysteresis behaviors that create considerable challenges to achieving real-time control accuracy and stability in dexterous hands. In order to address these challenges, this paper proposes a hierarchical control architecture that employs a fuzzy PID strategy to optimize the nonlinear control of pneumatic artificial muscles (PAMs). The FPGA-based hardware integrates a multi-channel digital-to-analog converter (DAC) and a multiplexed acquisition module, facilitating the independent actuation of 20 PAMs and the real-time monitoring of 20 joints. The software implements a fuzzy PID algorithm that dynamically adjusts PID parameters based on both the error and the error rate, thereby effectively managing the nonlinear behaviors of the hand. Experimental results demonstrate that the designed control system achieves high precision in controlling the angle of a single finger joint, with errors maintained within ±1°. In scenarios involving multi-finger cooperative grasping and biomimetic motion demonstrations, the system exhibits excellent synchronization and real-time performance. These results validate the efficacy of the fuzzy PID control strategy and confirm that the proposed system fulfills the precision and stability requirements for complex operational tasks, providing robust support for the application of PAM-driven multi-fingered dexterous hands.