Neural network position control of XY piezo actuator stage by visual feedback

This paper describes the visual feedback positional control of the XY piezo actuator stage (PAS). The XY PAS control system consists of four main components, i.e. XY PAS as controlled object, supply electronics for piezoelectric actuators (PEAs), microscope with digital camera for visualization and for measuring the actual position and a vision processing module in combination with a desktop PC, as processing hardware. XY PAS is fabricated by a photo structuring process from photosensitive glass, and PEAs are built-onto meet the request for its precise movement. It is evident from the electromechanical model of XY PAS, that accurate positioning of XY PAS is an exacting piece of work, due to the nonlinear hysteresis inherent in PEAs. Accordingly, two neural network control techniques were developed, i.e. the feedforward neural network controller (FFNNC) and the feedforward/feedback neural network controller (FF/FBNNC). Proposed neural network controllers are compared with the traditional linear controllers.