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Modeling and online parameter identification methods for Electrohydraulic Valvetrain Systems
Abstract
We consider an Electrohydraulic Valve System (EHVS) model with uncertain parameters that may possibly vary with time. This is a nonlinear third order system consisting of two clearly separated subsystems, one for piston position and the other for the chamber pressure. The nonlinearities involved are flow-pressure characteristics of the solenoid valves, the pressure dynamics of the chamber due to varying volume, and a variable damping nonlinearity. We develop a parametric model that is linear in the unknown parameters of the system using filtering. We deal with a nonlinear parameterization in the variable damping term using the Taylor approximation. We design two parameter identifiers which employs either a continuous-time unnormalized least-squares update law with a forgetting factor or a gradient update law. These update laws exponentially converges to the true parameters under a persistence of excitation condition, which is satisfied due to the periodic regime of operation of EHVS. We present simulation results that show good following of unknown parameters even with the presence of sensor noise. We also create a hybrid model of the EHVS and apply the identifiers. In the presence of the unmodelled dynamics we find there remains good following of the unknown parameters
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