Feasibility study of robust neural network motion tracking control of piezoelectric actuation systems for micro/nano manipulation
RIS ID
26536
Abstract
This paper presents a robust neural network motion tracking control methodology for piezoelectric actuation systems employed in micro/nano manipulation. This control methodology is proposed for tracking desired motion trajectories in the presence of unknown system parameters, non-linearities including the hysteresis effect, and external disturbances in the control systems. In this paper, the control methodology is established including the neural networks and a sliding scheme. In particular, the radial basis function neural networks are chosen in this study for function approximations. The stability of the closed-loop systems and convergence of the position and velocity tracking errors to zero are assured by the control methodology in the presence of the aforementioned conditions. Simulation results of the control methodology for tracking of a desired motion trajectory is presented. With the capability of motion tracking, the proposed control methodology can be utilised to realise high performance piezoelectric actuated micro/nano manipulation systems.
Publication Details
Liaw, H., Shirinzadeh, B., Alici, G. and Smith, J. (2008). Feasibility study of robust neural network motion tracking control of piezoelectric actuation systems for micro/nano manipulation. In S. Lee, I. Suh and M. Kim (Eds.), Lecture Notes in Control and Information Sciences: Recent Progress in Robotics: Viable Robotic Service to Human (vol.370) (pp. 5-19). New York: Springer.