๐ค AI Summary
This study addresses the challenge of achieving high-bandwidth control across wide operating conditions in robotic PMSM drives compromised by communication and computational delays. We propose a task-aware discrete modeling framework integrated with direct PI controller synthesis to overcome the limitations of conventional continuous-time design. By explicitly incorporating delay dynamics, this approach analytically determines optimal sampling frequencies and controller gains, enabling direct discrete controller design with guaranteed theoretical performance. The proposed method significantly reduces both sampling frequency and DC-bus voltage requirements. Simulation results and experiments on custom-built joint actuators validate its real-time efficacy in embedded systems, establishing a novel paradigm for high-performance robotic joint actuation under latency constraints.
๐ Abstract
The increasing dynamic demands of modern robotic joints require current controllers to achieve high bandwidth over wide operating ranges of speed, acceleration, and torque, where communication, computation, and discrete-time effects can no longer be neglected. Conventional PMSM current controllers are typically designed in continuous time and subsequently discretized, leaving the sampling frequency and the impact of implementation delays largely to heuristic selection and iterative validation. This paper introduces a task-aware, delay-extended discrete-time joint model that explicitly accounts for physical communication and computation delays and enables direct synthesis of a discrete PI current controller with prescribed bandwidth and delay guarantees throughout the operating envelope. The framework analytically determines the minimum required sampling frequency, controller gains, and DC-link voltage needed to satisfy the specified motor and joint performance. Simulations across a range of dynamic requirements validate the methodology and demonstrate substantially reduced sampling-frequency and DC-link-voltage requirements compared with conventional continuous-time-based design. Experiments on a newly developed custom robotic joint further validate the proposed framework under real embedded implementation conditions.