Design and stability analysis of a nonlinear controller for MRI-compatible pneumatic motors

Abstract

Among permissible magnetic resonance imaging (MRI) compatible actuators for surgical robots, turbine-based pneumatic motors are noticeably favorited due to its compact size, simpler structure, fast additively manufacturability, and continuous bidirectional motion ability. Yet, the system dynamics of pneumatic motors, especially pneumatic nonlinearity, is often neglected and simple PID control is used, resulting in low system bandwidth (~0.5 Hz). To tackle this obstacle, this paper proposes a model-based nonlinear control method for MRI-compatible pneumatic motors. Dynamic models for a pneumatic motor previously designed by the author are developed first, followed by establishment of the nonlinear feedback controller. An error based Lyapunov candidate function is designed and mathematically proved to be globally uniformly asymptotically stable, guaranteeing desired accuracy. Experiment control tests demonstrate that the proposed control method can achieve satisfactorily better tracking accuracy than a conventional model-independent PID controller with respect to amplitude attenuation and phase delay.

Modeling, Analysis and Evaluation of a Novel Compact 6-DoF 3-RRRS Needle Biopsy Robot

“…Many show deficiencies in operating area and reachable collision-free workspace, which precludes them from general purpose applications [13]. Additionally, with the well-accepted assumption that surgeries are preformed slowly [25], current works mainly focus on robot kinematic modeling and position control with image registration, without Jacobian analysis, which is especially critical for parallel robots to ensure the surgical robot works in a singularity-free workspace [26]. The Jacobian analysis also allows robot speed control to further improve the surgery progress.…”