A method that uses input/output measurements is developed for the estimation of the coefficients of stochastic Time-varying AutoRegressive Moving Average with eXogeneous imputs (TARMAX) models. The TARMAX coefficients are expressed as linear combinations of a set of pre-selected functions. The model coefficients estimation method is fully based on linear operations, does not require initial guess values and is suitable for micro-computer implementation. The good performance of the estimation method is verified through numerical examples. A TARMAX model is also used to capture the dynamics of a detailed highly nonlinear model of an automobile hydraulic active suspension system. The TARMAX model is used to relate a desired force provided by a corner processor to the actual force generated by the hydraulic actuator. The TARMAX model is shown to provide good signal prediction ability.

Issue Section:
Technical Briefs
Keywords:
autoregressive moving average processes, nonlinear systems, parameter estimation
Topics:
Actuators, Automobiles, Dynamics (Mechanics), Errors, Modeling, Nonlinear systems, Polynomials, Signals, Suspension systems, Algorithms, Computers, Corners (Structural elements), Parameter estimation, Performance evaluation
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Copyright © 2002
 by ASME
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