Model-based control for SMA actuators : to advance minimal invasive surgery

Aansturing van robotische katheter voor minimaal invasieve operatie

Fraction-based input modification for fast SMA-actuation

Shape Memory Alloy actuators are microactuators that are known for their high actuation-force and -strain. Limiting the application of Shape Memory Alloy actuators is the lack of suitable control algorithms that can deal with the highly non-linear dynamics of the actuator. The latter suffers from hysteresis and is characterized by the changing crystallographic structure of Shape Memory Alloy. In this work, smart input constraints are developed to prevent overcooling and overheating, and by that, improve the tracking behavior of the actuator

Physical modeling of macroscopic phase transition behavior for nickel titanium shape memory alloy (SMA) wires

\u3cp\u3eThe macroscopic behavior of Nickel Titanium Shape Memory Alloy (SMA) wires suffers from hysteresis. This is related to the fraction of material that is in detwinned martensite crystallographic orientation. In this work, a novel physical model is proposed that describes the fraction of transformed material on a macroscopic level. The model is history-free, and hence, is ideal to implement in model-based control strategies.\u3c/p\u3

An evaluation framework for inverse hysteresis models

Control schemes employing inverse-based hysteresis compensation are successful in accurate position control of smart material actuators. However, the effectiveness of the inverse hysteresis model in cancelling hysteresis is not addressed in the evaluation of these control schemes. Classical methods rely on closed-loop tracking error analysis which does not allow evaluation of the inverse model independent of the controller. This leads to lack of a deterministic measure of the amount of hysteresis cancelled by the model, while the influence of an inaccurate model on the overall tracking error also remains unclear. This paper proposes a framework to verify the effectiveness and accuracy of inverse hysteresis models by quantifying the hysteresis non-linearities remaining after hysteresis compensation. Further, by estimating the linear and residual non linear dynamics, valuable information is provided for controller design. The framework is experimentally validated for a Shape Memory Alloy (SMA) actuator. The framework can be seen as a tool to explore and compare different inverse hysteresis models prior to controller design

Image-based estimation and nonparametric modeling:Towards enhanced geometric calibration of an X-ray system

\u3cp\u3eGeometric calibrations of medical imaging systems are crucial to allow for advanced (X-ray) imaging techniques. Developments in medical procedures, lightweight system design and the growing costs of healthcare, leads to the desire for simpler and faster calibration approaches. The aim of this paper is to present a novel approach to enhance system calibrations for a wide range of imaging applications. The method is based on the introduction of small markers within the line of sight of the system, by virtue of a small mechanical adjustment to the system. By detecting markers in the X-ray images, displacements between the systems X-ray source and detector are in-situ measured. Additionally, the approach can be used to obtain nonparametric models of the dynamics of the mechanical system, enabling advanced observer-based estimation approaches. The potential of the method is illustrated by experimental results.\u3c/p\u3