Feedback for nonlinear system identification

Motivated by neuronal models from neuroscience, we consider the system identification of simple feedback structures whose behaviors include nonlinear phenomena such as excitability, limit-cycles and chaos. We show that output feedback is sufficient to solve the identification problem in a two-step procedure. First, the nonlinear static characteristic of the system is extracted, and second, using a feedback linearizing law, a mildly nonlinear system with an approximately-finite memory is identified. In an ideal setting, the second step boils down to the identification of a LTI system. To illustrate the method in a realistic setting, we present numerical simulations of the identification of two classical systems that fit the assumed model structure.Comment: 18th European Control Conference (ECC), Napoli, Italy, June 25-28 201

Chassis Dynamometer Torque Control System Design by Direct Inverse Compensation

This paper presents a methodology for the design of a robust torque control system for a transient 1.2m (48in) dia, 120 kW, DC Chassis Dynamometer. The method includes system identification of the nonlinear dynamometer torque supply system, linearisation by direct inverse compensation, and linear identification of both the compensated and uncompensated plants. A combined feedforward-feedback control structure is proposed and robust feedback controllers are designed using a fixed-order parameter space method. Keywords: Chassis Dynamometer, Direct Inverse Control, Feedback,Feedforward, Identification, Parameter Space, Multiplicative Uncertainty, Nonlinear, Road-Load Simulation

An experimental study of nonlinear dynamic system identification

A technique based on the Minimum Model Error optimal estimation approach is employed for robust identification of a nonlinear dynamic system. A simple harmonic oscillator with quadratic position feedback was simulated on an analog computer. With the aid of analog measurements and an assumed linear model, the Minimum Model Error Algorithm accurately identifies the quadratic nonlinearity. The tests demonstrate that the method is robust with respect to prior ignorance of the nonlinear system model and with respect to measurement record length, regardless of initial conditions

Identification of Nonlinear Damping Using Nonlinear Subspace Method

In this paper, the identification problem is discussed for damping nonlinearity. In practical applications, nonlinear damping is widespread, which is inevitable in the vibration response. Within the wide range of nonlinear damping mechanisms, friction is surely one of the most common, and with a high impact on the dynamical behavior of structures. Two common kinds of friction are investigated: quadratic friction and Coulomb friction. Nonlinear damping parameters are identified by nonlinear subspace identification, where the damping nonlinearity of the system is considered as a feedback force applied to the underlying linear system and is identified utilizing the time domain data. Two simulation examples are conducted to verify the effectiveness of the method. Results confirm the effectiveness of the methodology in identifying damping nonlinearities

Comparison between control-based continuation and phase-locked loop methods for the identification of backbone curves and nonlinear frequency responses

Control-based continuation (CBC) and phase-locked loops (PLL) are two experimental testing methods that have demonstrated great potential for the non-parametric identification of key nonlinear dynamic features such as nonlinear frequency responses and backbone curves. Both CBC and PLL exploit stabilizing feedback control to steer the dynamics of the tested system towards the responses of interest and overcome important difficulties experienced when applying conventional testing methods such as sine sweeps to nonlinear systems. For instance, if properly designed, the feedback controller can prevent the system from exhibiting untimely transitions between coexisting responses or even losing stability due to bifurcations. This contribution aims to highlight the similarities that exist between CBC and PLL and present the first thorough comparison of their capabilities. Comparisons are supported by numerical simulations as well as experimental data collected on a conceptually simple nonlinear structure primarily composed of a thin curved beam. The beam is doubly clamped and exhibits nonlinear geometric effects for moderate excitation amplitudes

Comparison between control-based continuation and phase-locked loop methods for the identification of backbone curves and nonlinear frequency responses

Control-based continuation (CBC) and phase-locked loops (PLL) are two experimental testing methods that have demonstrated great potential for the non-parametric identification of key nonlinear dynamic features such as nonlinear frequency responses and backbone curves. Both CBC and PLL exploit stabilizing feedback control to steer the dynamics of the tested system towards the responses of interest and overcome important difficulties experienced when applying conventional testing methods such as sine sweeps to nonlinear systems. For instance, if properly designed, the feedback controller can prevent the system from exhibiting untimely transitions between coexisting responses or even losing stability due to bifurcations. This contribution aims to highlight the similarities that exist between CBC and PLL and present the first thorough comparison of their capabilities. Comparisons are supported by numerical simulations as well as experimental data collected on a conceptually simple nonlinear structure primarily composed of a thin curved beam. The beam is doubly clamped and exhibits nonlinear geometric effects for moderate excitation amplitudes