Multi-Objective Optimization of Design Parameters to Improve Dynamic Performances of Distributed Actuation Mechanism

The distributed actuation mechanism (DAM) is inspired by the motion of biological muscles and enables efficient modulation between speed and force through a variable gearing concept. This study proposes an advanced modeling-based multi-objective optimization framework that enhances the dynamic performance of a DAM-based manipulator by simultaneously improving its end-effector velocity and payload capacity. The kinematic and dynamic characteristics of the DAM are mathematically modeled to capture the interactions among design parameters, and a high-fidelity multibody dynamics model is developed using RecurDyn. Then, a sequential quadratic programming (SQP) algorithm implemented in MATLAB is employed to perform optimization under geometric and physical constraints. The results demonstrate that the proposed optimization method achieved increases of approximately 46.5% in maximum velocity and over 40% in maximum payload, confirming the effectiveness of the advanced modeling-based optimization strategy. It was also found that link-length ratios and hinge offsets play critical roles in determining the DAM’s dynamic behavior. The proposed framework provides a systematic and practical approach for integrating mathematical modeling with design optimization and offers valuable guidelines for improving the structural design and performance of distributed-actuation-based robotic manipulators.