论文信息 - Subspace identification method for ankle mechanics

Subspace identification method for ankle mechanics

Presents results a new algorithm for modeling biological systems using a state space approach. One of the MIMO Output-Error State Space identification (MOESP) family of algorithms (see M. Verhaegen and P. Dewilde, Int. J. Control, vol. 55, no. 5, p. 1187-1210, 1992) has been adapted to model the linear part of human ankle mechanics. A mixed causal/anti-causal state space model was calculated to examine the relationship between torque and position of the ankle. Simulated and real data are used to show that the method yields parametric models for ankle mechanics that describe behavior as well as nonparametric models. However, the parametric models obtained using the MOESP identification method have many fewer parameters.

[1] Michel Verhaegen. A Subspace Model Identification Solution to the Identification of Mixed Causal, Anti-Causal LTI Systems , 1996, SIAM J. Matrix Anal. Appl..

[2] Patrick Dewilde,et al. Subspace model identification Part 1. The output-error state-space model identification class of algorithms , 1992 .

[3] M. Verhaegen. Subspace model identification Part 2. Analysis of the elementary output-error state-space model identification algorithm , 1992 .

[4] I. Hunter,et al. Dynamics of human ankle stiffness: variation with mean ankle torque. , 1982, Journal of biomechanics.