On the identification of Hammerstein systems with time-varying parameters.
A growing emphasis on the analysis of time-varying systems has intensified the need for simpler and more efficient identification methods for these systems. In this contribution, we examine the time-varying Hammerstein structure, comprising a memoryless nonlinearity with time-varying parameters followed by a time-varying linear filter. Two existing approaches for the identification of these systems, ensemble approaches and basis expansion methods, are combined as a single algorithm to give a much improved estimation tool. The proposed algorithm, applied to data from a simulation of a time-varying Hammerstein system, is used to construct models of the reflex contribution to joint stiffness and the results obtained are compared to those using the basis expansion method alone.
Ikharia
Bashiru I
BI
Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW, Calgary, Alberta, T2N 1N4, Canada.
Westwick
David T
DT
D000465:Algorithms; D000843:Ankle Joint / Q000502:physiology; D008954:Models, Biological; D012018:Reflex; D019415:Torque