Affiliation:
1. School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, China
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.
Cited by
6 articles.
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