Feasibility study of robust neural network motion tracking control of piezoelectric actuation systems for micro/nano manipulation

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 of 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. Particularly,

the radial basis function neural networks are chosen in this study

for function approximations. 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.