scholarly journals Stochastic Estimation of the Multi-Variable Mechanical Impedance of the Human Ankle With Active Muscles

2010 ◽  
Author(s):  
Mohammad A. Rastgaar ◽  
Patrick Ho ◽  
Hyunglae Lee ◽  
Hermano Igo Krebs ◽  
Neville Hogan
Keyword(s):  
Muscle Activation ◽  
Transfer Functions ◽  
Linear Time ◽  
Plantar Flexion ◽  
Mechanical Impedance ◽  
Linear Time Invariant ◽  
Ankle Muscles ◽  
Human Ankle ◽  
Time Histories ◽  
The Difference

This article compares stochastic estimates of multi-variable human ankle mechanical impedance when ankle muscles were fully relaxed, actively generating ankle torque or co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Muscle activation levels were monitored electromyographically and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when it was worn by a human subject, the difference between these functions providing an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in both DP and IE directions.

scholarly journals Stochastic Estimation of Multi-Variable Human Ankle Mechanical Impedance

2009 ◽  
Author(s):  
Mohammad A. Rastgaar ◽  
Patrick Ho ◽  
Hyunglae Lee ◽  
Hermano Igo Krebs ◽  
Neville Hogan
Keyword(s):  
Transfer Functions ◽  
Linear Time ◽  
Plantar Flexion ◽  
Mechanical Impedance ◽  
Linear Time Invariant ◽  
Human Ankle ◽  
Time Histories ◽  
The Difference ◽  
Time Invariant ◽  
Impedance Functions

This article presents preliminary stochastic estimates of the multi-variable human ankle mechanical impedance. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Time histories of the torques in Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions and the associated angles of the ankle were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot and when the Anklebot was worn by a human subject. The difference between these impedance functions provided an estimate of the mechanical impedance of the ankle. High coherence was observed over a frequency range up to 30 Hz, indicating that this procedure yielded an accurate measure of ankle mechanical impedance in DP and IE directions.

Stochastic Estimation of Human Ankle Mechanical Impedance in Lateral/Medial Rotation

2014 ◽  
Author(s):  
Evandro M. Ficanha ◽  
Mohammad Rastgaar
Keyword(s):  
Degrees Of Freedom ◽  
Muscle Activation ◽  
Transfer Functions ◽  
Linear Time ◽  
Mechanical Impedance ◽  
Linear Time Invariant ◽  
Ankle Impedance ◽  
Human Ankle ◽  
Medial Rotation ◽  
The Difference

This article compares stochastic estimates of human ankle mechanical impedance when ankle muscles were fully relaxed and co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle to provide torque perturbations. Surface electromyography (EMG) was used to monitor muscle activation levels and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the lateral/medial (LM) directions were recorded. The results also compared with the ankle impedance in inversion-eversion (IE) and dorsiflexion-plantarflexion (DP). Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when a human subject wore it; the difference between these functions provided an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in all degrees of freedom of ankle.

Complementary Sensitivity Design of PID Controllers for Arbitrary-Order Transfer Functions With Time Delay

2008 ◽  
Author(s):  
Tooran Emami ◽  
John M. Watkins
Keyword(s):  
Time Delay ◽  
Transfer Functions ◽  
Linear Time ◽  
Order System ◽  
Pid Controllers ◽  
Single Input Single Output ◽  
Linear Time Invariant ◽  
Single Output ◽  
Plant Transfer ◽  
Time Invariant

A graphical technique for finding all proportional integral derivative (PID) controllers that stabilize a given single-input-single-output (SISO) linear time-invariant (LTI) system of any order system with time delay has been solved. In this paper a method is introduced that finds all PID controllers that also satisfy an H∞ complementary sensitivity constraint. This problem can be solved by finding all PID controllers that simultaneously stabilize the closed-loop characteristic polynomial and satisfy constraints defined by a set of related complex polynomials. A key advantage of this procedure is the fact that it does not require the plant transfer function, only its frequency response.

Optimal Nonlinear Estimation of Linear Stochastic Systems: The Multivariable Extension

1996 ◽  
Vol 118 (2) ◽  
pp. 350-353 ◽  
Author(s):  
M. A. Hopkins ◽  
H. F. VanLandingham
Keyword(s):  
Stochastic Systems ◽  
Transfer Functions ◽  
Mimo Systems ◽  
Linear Time ◽  
Nonlinear Method ◽  
Single Input Single Output ◽  
Linear Time Invariant ◽  
Single Output ◽  
Time Invariant ◽  
Time Systems

This paper extends to multi-input multi-output (MIMO) systems a nonlinear method of simultaneous parameter and state estimation that appeared in the ASME JDSM&C (September, 1994), for single-input single-output (SISO) systems. The method is called pseudo-linear identification (PLID), and applies to stochastic linear time-invariant discrete-time systems. No assumptions are required about pole or zero locations; nor about relative degree, except that the system transfer functions must be strictly proper. In the earlier paper, proofs of optimality and convergence were given. Extensions of those proofs to the MIMO case are also given here.

Parameter Uncertainty Modeling Using the Multidimensional Principal Curves

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
M. Sepasi ◽  
F. Sassani ◽  
R. Nagamune
Keyword(s):  
Transfer Functions ◽  
Linear Time ◽  
Optimization Technique ◽  
Parametric Uncertainty ◽  
Uncertainty Modeling ◽  
Principal Component ◽  
Linear Matrix ◽  
Linear Time Invariant ◽  
Uncertain Variables ◽  
Uncertainty Model

This paper proposes a technique to model uncertainties associated with linear time-invariant systems. It is assumed that the uncertainties are only due to parametric variations caused by independent uncertain variables. By assuming that a set of a finite number of rational transfer functions of a fixed order is given, as well as the number of independent uncertain variables that affect the parametric uncertainties, the proposed technique seeks an optimal parametric uncertainty model as a function of uncertain variables that explains the set of transfer functions. Finding such an optimal parametric uncertainty model is formulated as a noncovex optimization problem, which is then solved by a combination of a linear matrix inequality and a nonlinear optimization technique. To find an initial condition for solving this nonconvex problem, the nonlinear principal component analysis based on the multidimensional principal curve is employed. The effectiveness of the proposed technique is verified through both illustrative and practical examples.

scholarly journals Interpretation of the Directional Properties of Voluntarily Modulated Human Ankle Mechanical Impedance

2010 ◽  
Author(s):  
Patrick Ho ◽  
Hyunglae Lee ◽  
Mohammad A. Rastgaar ◽  
Hermano Igo Krebs ◽  
Neville Hogan
Keyword(s):  
Muscle Activation ◽  
Mechanical Impedance ◽  
In Vivo Studies ◽  
General Representation ◽  
Quantitative Characterization ◽  
Ankle Impedance ◽  
Human Ankle ◽  
Electromyographic Recording

This article presents the results of two in-vivo studies providing measurements of human static ankle mechanical impedance. Accurate measurements of ankle impedance when muscles were voluntarily activated were obtained using a therapeutic robot, Anklebot, and an electromyographic recording system. Important features of ankle impedance, and their variation with muscle activity, are discussed, including magnitude, symmetry and directions of minimum and maximum impedance. Voluntary muscle activation has a significant impact on ankle impedance, increasing it by up to a factor of three in our experiments. Furthermore, significant asymmetries and deviations from a linear two-spring model are present in many subjects, indicating that ankle impedance has a complex and individually idiosyncratic structure. We propose the use of Fourier series as a general representation, providing both insight and a precise quantitative characterization of human static ankle impedance.

scholarly journals Analysis and Experimental Evaluation of Power Line Transmission Parameters for Power Line Communication

2015 ◽  
Vol 15 (2) ◽  
pp. 64-71 ◽  
Author(s):  
P. Mlynek ◽  
J. Misurec ◽  
M. Koutny ◽  
R. Fujdiak ◽  
T. Jedlicka
Keyword(s):  
Transfer Functions ◽  
Linear Time ◽  
Power Line ◽  
Power Line Communication ◽  
Numerical Verification ◽  
Electrical Cable ◽  
Linear Time Invariant ◽  
Transmission Parameters ◽  
Channel Frequency Response ◽  
Time Invariant

Abstract The article describes a way of evaluating the power line channel frequency response and input impedance by means of the linear time-invariant (LTI) power line generator. Two possible methods are introduced for the calculation of primary parameters: the first method depends on the physical realization and physical dimension of the cable, and the second method is derived from the data provided by typical electrical cable manufacturers. Based on these methods, a comparison of transfer functions was made. This is followed by measurement evaluation and numerical verification on a simple topology

scholarly journals Extending the Root-Locus Method to Fractional-Order Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-13 ◽  
Author(s):  
Farshad Merrikh-Bayat ◽  
Mahdi Afshar
Keyword(s):  
Fractional Order ◽  
Transfer Functions ◽  
Linear Time ◽  
Rational Functions ◽  
Fractional Order Systems ◽  
Root Locus ◽  
Linear Time Invariant ◽  
Locus Method ◽  
Linear Time Invariant Systems ◽  
Time Invariant

The well-known root-locus method is developed for special subset of linear time-invariant systems known as fractional-order systems. Transfer functions of these systems are rational functions with polynomials of rational powers of the Laplace variables. Such systems are defined on a Riemann surface because of their multivalued nature. A set of rules for plotting the root loci on the first Riemann sheet is presented. The important features of the classical root-locus method such as asymptotes, roots condition on the real axis, and breakaway points are extended to fractional case. It is also shown that the proposed method can assess the closed-loop stability of fractional-order systems in the presence of a varying gain in the loop. Three illustrative examples are presented to confirm the effectiveness of the proposed algorithm.

Automatic Calibration of the 3D Vector Magnetometer

2012 ◽  
Vol 591-593 ◽  
pp. 1256-1259
Author(s):  
Long Li ◽  
Zhang He
Keyword(s):  
Linear Time ◽  
Three Dimensional ◽  
Calibration Method ◽  
Model Parameters ◽  
Linear Time Invariant ◽  
Vector Magnetometer ◽  
Calibration Algorithm ◽  
Mobile Consumer ◽  
The Difference ◽  
Consumer Devices

Embedded sensors are an emerging trend in mobile consumer devices. In this work a new algorithm is derived for the onboard calibration of three-axis magnetometers. The proposed calibration method is written in the sensor frame, and compensates for the combined effect of all linear time-invariant distortions, namely soft iron, hard iron, three-dimensional sensor non-orthogonally, scale factors, null-shift, arbitrary bias, among others. The new algorithm can be separated into two steps: In the first step, obtain the ellipsoid fitting parameters from comparing the difference between the measured value and the actual vector. In a second step, a calibration algorithm is adopted to compensate for magnetometers distortions. According to the model parameters the measured data is corrected to improve the precision of magnetometer. Simulation and experimental results with sensors data are presented and discussed, supporting the application of the algorithm to commercial and military platforms.

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