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Design and Validation of a Novel Model Reference Adaptive Algorithm to Control ETB for Drive-by-wire Applications
- Mario di Bernardo - Università degli Studi Napoli Federico II ,
- Umberto Montanaro - Università degli Studi Napoli Federico II ,
- Stefania Santini - Università degli Studi Napoli Federico II ,
- Alessandro di Gaeta - Istituto Motori, Consiglio Nazionale delle Ricerche ,
- Veniero Giglio - Istituto Motori, Consiglio Nazionale delle Ricerche
ISSN: 1946-3995, e-ISSN: 1946-4002
Published June 15, 2009 by SAE International in United States
Citation: di Bernardo, M., Montanaro, U., Santini, S., di Gaeta, A. et al., "Design and Validation of a Novel Model Reference Adaptive Algorithm to Control ETB for Drive-by-wire Applications," SAE Int. J. Passeng. Cars – Mech. Syst. 2(1):1268-1284, 2009, https://doi.org/10.4271/2009-01-1780.
In automotive industry the Electronic Throttle Body (ETB) plays a crucial role in drive-by-wire operations since it controls the incoming air into the engine and so the produced torque. This implies the performances of the vehicle in terms of traction, emissions, idle speed regime, cold starting management, thermal transient and smoother movement during tip/in tip/out, strongly depends on the precise control of this device . Despite its apparent simplicity, the behavior of the ETB is affected by many nonlinearities and uncertain parameters which can dramatically alter its dynamics. In order to cope the unwanted nonlinear phenomenons (stick-slip motion, hysteresis, hunting, impact, caos), sophisticated model based control strategies and compensators are proposed in the literature. A time consuming identification parameters of the throttle is fundamental for these approaches and it is the main drawback for their application.
The aim of the paper is to show the efficiency of a model reference adaptive algorithm, named LQ-MCS (Linear Quadratic-Minimal Control Synthesis), to control the throttle plate position. The main feature of this controller is that minimal synthesis is needed to implement the strategy. Specifically only a rough nominal linear model of the
plant is required to impose the dynamical behavior of the reference model. By means of a proper experimental setup, the adaptive controller is synthesized and validated experimentally.