کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10400102 890878 2005 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Online identification and nonlinear control of the electrically stimulated quadriceps muscle
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
پیش نمایش صفحه اول مقاله
Online identification and nonlinear control of the electrically stimulated quadriceps muscle
چکیده انگلیسی
A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Control Engineering Practice - Volume 13, Issue 9, September 2005, Pages 1207-1219
نویسندگان
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