Haptics : generic stability and beyond

In this report we study haptic interaction with slowly updated virtual environments (VEs). Such systems can become unstable due to phase lag introduced in the control loop by the delay of the VE simulation. Because of the unpredictable nature of the VEs, a force feedback control framework is required that can guarantee the stability of the haptic interaction in the absence of a model of the VE. In [1] a passivity condition for such a framework is presented, based on multirate wave variable control and filter banks, however up to now no filter design is presented which actually obeys these passivity conditions. Our contribution is an optimization algorithm to derive filters which guarantee stability. The goal is to present an optimization algorithm which gives an engineer freedom in designing the filters. By doing this we are able to present a filter bank which has guaranteed stability, while giving special attention to the boundaries in the human sensory system and the rejection of measurement noise. We investigate performance by comparing transferred admittance and stiffness; both analytically and experimentally. We present an optimization algorithm which generates guaranteed stable filter banks. The filter bank derived using the proposed optimization algorithm has superior performance compared to previous derived filter banks

Haptics : generic stability and beyond

In this report we study haptic interaction with slowly updated virtual environments (VEs). Such systems can become unstable due to phase lag introduced in the control loop by the delay of the VE simulation. Because of the unpredictable nature of the VEs, a force feedback control framework is required that can guarantee the stability of the haptic interaction in the absence of a model of the VE. In [1] a passivity condition for such a framework is presented, based on multirate wave variable control and filter banks, however up to now no filter design is presented which actually obeys these passivity conditions. Our contribution is an optimization algorithm to derive filters which guarantee stability. The goal is to present an optimization algorithm which gives an engineer freedom in designing the filters. By doing this we are able to present a filter bank which has guaranteed stability, while giving special attention to the boundaries in the human sensory system and the rejection of measurement noise. We investigate performance by comparing transferred admittance and stiffness; both analytically and experimentally. We present an optimization algorithm which generates guaranteed stable filter banks. The filter bank derived using the proposed optimization algorithm has superior performance compared to previous derived filter banks

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

The 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

Improved automatic exposure control using morphology-based disturbance recognition

In medical X-ray imaging, the detector intensity heavily influences the signal-to-noise ratio, and thus the image quality. Consequently, image quality and patient dose are dependent on the performance of the Automatic Exposure Control. Introducing large opaque objects to the image, which can be considered disturbances for the dose control, leads to a loss of image quality (overexposed tissue) as well as an increased patient dose. The effect of scatter-radiation makes it difficult to exclude these disturbances from the image using simple thresholding. In this work, a morphology-based filter is proposed as a pre-processing step for the Automatic Exposure Control leading to a superior disturbance exclusion. The algorithm has been verified in a real-time environment and it is shown to be robust against large disturbances in the X-ray images