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Journal of Dynamic Systems, Measurement, and Control | Volume 128 | Issue 2 | TECHNICAL PAPERS
TECHNICAL PAPERS

The Extended Variable Structure Filter

[+] Author and Article Information
Saeid Habibi

 University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada, S7N 5A9SaeiḏHabibi@engr.usask.ca

J. Dyn. Sys., Meas., Control 128(2), 341-351 (Apr 19, 2005) (11 pages) doi:10.1115/1.2194070 History: Received June 26, 2003; Revised April 19, 2005
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Citing Articles

In this paper, a new method for state estimation, referred to as the variable structure filter (VSF), is briefly reviewed. The VSF method is model based and has been formulated for its application to linear systems. It provides a means of explicitly defining the level of uncertainty in the dynamic model used by the filter, thus allowing for tradeoff between the performance indicators of the filter. This trade-off feature is not generally explicitly available in some of the more established concepts used for state estimation. In this paper, an extension to the VSF method for its application to nonlinear systems is proposed and referred to as the extended variable structure filter (EVSF). The derivation of EVSF and its application to a nonlinear robotic example is provided.
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Figures

Grahic Jump Location
+Measured angular position of the robotic arm
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Measured angular position of the robotic arm
Figure 3

Measured angular position of the robotic arm

Grahic Jump Location
+Simple robotic arm
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Simple robotic arm
Figure 2

Simple robotic arm

Grahic Jump Location
+(a) Estimated and actual states associated with angular position and (b) estimated and actual states associated with angular velocity
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(a) Estimated and actual states associated with angular position and (b) estimated and actual states associated with angular velocity
Figure 4

(a) Estimated and actual states associated with angular position and (b) estimated and actual states associated with angular velocity

Grahic Jump Location
+(a) State estimation error associated with angular position and (b) state estimation error associated with angular velocity
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(a) State estimation error associated with angular position and (b) state estimation error associated with angular velocity
Figure 5

(a) State estimation error associated with angular position and (b) state estimation error associated with angular velocity

Grahic Jump Location
+Convergence of the estimated state trajectory due to the VSF action
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Convergence of the estimated state trajectory due to the VSF action
Figure 1

Convergence of the estimated state trajectory due to the VSF action

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