Control Studies for Nanopositioning

Abstract

This thesis presents a study of feedback controllers for nanopositioning stages, commonly employed in applications such as atomic force microscopy (AFM) and nanofabrication, amongst other precision positioning applications. These systems are characterised by their poorly damped dynamics and nonlinear behaviour due to hysteresis and thermal drift in the actuators. The focus of this work is on the discrete-time design and implementation of controllers, with a particular emphasis on model-based designs. Classical control methods are considered, and the use of the Observer-based Offset-free Internal Model Control structure is investigated to compensate for the system's characteristics. The main contribution of this thesis is the development and implementation of the Observer-based Offset-free Internal Model Control structure for nanopositioning stages. This structure guarantees offset-free characteristics and enables faster speed positioning compared to state-of-the-art control schemes. The appropriate models are identified, and controllers are designed and implemented in commercial single-axis and 2-axis nanopositioning prototypes. Experimental results demonstrate the effectiveness of the proposed controllers in achieving zero steady-state error and high-bandwidth designs. Specifically, the designed controllers achieve bandwidths of up to 67\% with respect to the resonance of the nanopositioning systems, with experimental results supporting the proposed controllers. Moreover, this thesis also includes a study of high-bandwidth transfer function models for various stages, including position and force feedback signals. In general, this work provides insight into the design and implementation of feedback controllers for nanopositioning stages, which are essential to achieve high-speed rates and position accuracy in precision positioning applications.

Date of Award	15 Mar 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	William Heath (Main Supervisor) & Joaquin Carrasco Gomez (Co Supervisor)