Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dy 2013
DOI: 10.1115/dscc2013-3701
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A Method for Selecting Velocity Filter Cutoff Frequency for Maximizing Impedance Width Performance in Haptic Interfaces

Abstract: This paper analyzes the effect of velocity filtering cut-off frequency on the Z-width performance in haptic interfaces. Finite Difference Method (FDM) cascaded with a lowpass filter is the most commonly used technique for estimating velocity from position data in haptic interfaces. So far, there is no prescribed method for obtaining the FDM+filter cut-off frequency that will maximize the Z-width performance. We present a simulation based method to demonstrate that there exists such an ideal FDM+filter cut-off … Show more

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Cited by 1 publication
(2 citation statements)
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“…We consider a haptic system with ‘fixed’ system parameters: m = 250 g, b = 0.5 Ns/m, c = 0.1 N, Δ = 0.00005 m, T = 0.001 s, and t d = 0.003 s. These parameters are determined by hardware and are not easily changed. The values were chosen to represent currently existing haptic devices, mechatronic interfaces, and amplifier dynamics (Chawda et al, 2014; Diolaiti et al, 2006; Gil et al, 2009). We consider the ‘control’ parameters K , B , f 0 , and n ; these parameters are determined by software and are easily manipulated.…”
Section: Stability and Quantization-error Regionsmentioning
confidence: 99%
See 1 more Smart Citation
“…We consider a haptic system with ‘fixed’ system parameters: m = 250 g, b = 0.5 Ns/m, c = 0.1 N, Δ = 0.00005 m, T = 0.001 s, and t d = 0.003 s. These parameters are determined by hardware and are not easily changed. The values were chosen to represent currently existing haptic devices, mechatronic interfaces, and amplifier dynamics (Chawda et al, 2014; Diolaiti et al, 2006; Gil et al, 2009). We consider the ‘control’ parameters K , B , f 0 , and n ; these parameters are determined by software and are easily manipulated.…”
Section: Stability and Quantization-error Regionsmentioning
confidence: 99%
“…More aggressive low-pass filtering of the velocity estimate can mitigate the negative effects of the quantization error, but can affect the sampled-data passivity/stability. Chawda et al (2014) presented a method to choose a low-pass filter cut-off frequency that maximizes the renderable range of virtual stiffness and damping for an identified model of a haptic display for an exogenous human-interaction model using numerical simulation. Their analysis does not consider the effect of human coupling on the stability or quantization-error limit cycles or present analytical sampled-data passivity or quantization-error results.…”
Section: Introductionmentioning
confidence: 99%