Direct identification of continuous-time linear parameter-varying input/output models

System Identification of Linear Parameter Varying State-space Models

This chapter examines the estimation of multivariable linear models for which the parameters vary in a time-varying manner that depends in an affine fashion on a known or otherwise measured signal. These locally linear models which depend on a measurable operating point are known as linear parameter varying (LPV) models. The contribution here relative to previous work on the topic is that in th...

Parameter Identification: Continuous Time

The purpose of this chapter is to present the design, analysis, and simulation of a wide class of algorithms that can be used for online parameter identification of continuous-time plants. The online identification procedure involves the following three steps. Step 1. Lump the unknown parameters in a vector θ∗ and express them in the form of the parametric model SPM, DPM, B-SPM, or B-DPM. Step ...

The Problem of Identification in Finite Parameter Continuous Time Models

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

Dynamic joint stiffness is a dynamic, nonlinear relationship between the position of a joint and the torque acting about it, which can be used to describe the biomechanics of the joint and associated limb(s). This paper models and quantifies changes in ankle dynamic stiffness and its individual elements, intrinsic and reflex stiffness, in healthy human subjects during isometric, time-varying (T...

Direct Identification of Continuous-Time LPV Input/Output Models

Controllers in the linear parameter-varying (LPV) framework are commonly designed in continuoustime (CT) requiring accurate and low-order CT models of the system. However, identification of continuous-time LPV models is largely unsolved, representing a gap between the available LPV identification methods and the needs of control synthesis. In order to bridge this gap, direct identification of C...