Position Control of a Six Degree of Freedom Platform Based on Iterative Learning and Pre Compensation Mechanism

This paper focuses on the research and development of an advanced control strategy for Six-DOF Stewart platforms, aiming to enhance their motion accuracy and dynamic performance. To address the challenges posed by the system's inherent nonlinearity, coupling, and dynamic complexity, a PD-type Iterative Learning Control (ILC) approach is proposed, incorporating a pre-compensation mechanism and a high-order variable gain-based forgetting factor. The study details the design and implementation of this control method, which leverages iterative learning to refine tracking precision and dynamic behavior over successive cycles. Through comprehensive simulations, the effectiveness of the proposed strategy is validated, demonstrating significant improvements in tracking accuracy and overall system performance. The results highlight the potential of this approach for applications in aerospace, robotics, and precision machining, where high precision and robust dynamic control are critical.