Feedback Linearizing Air/Fuel-Ratio Controller

Guzzella, Lino; Simons, Michael R.; Geering, Hans P.

doi:10.1016/s1474-6670(17)58941-7

Cited by 3 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, a Takagi-SugenoŠs fuzzy model is derived from which an observer is developed. In [7] a dynamic feedback linearization approach is proposed for the air-fuel ratio system considering that some of the parameters of the nonlinear dynamical model are time invariant or exhibit slow dynamics. In [8] a neural network model of the engine and a neural network controller are developed based on the idea of approximate dynamic programming to achieve optimal control.…”

Section: Introductionmentioning

confidence: 99%

Flatness-based embedded control of air-fuel ratio in combustion engines

Rigatos¹,

Siano²,

Arsie³

2014

AIP Conference Proceedings

View full text Add to dashboard Cite

Articles you may be interested inFlatness-based embedded adaptive fuzzy control of spark ignited engines AIP Conf. Proc. 1618, 241 (2014); 10.1063/1.4897720 Flatness-based nonlinear embedded control and filtering for spark-ignited engines AIP Conf. Proc. 1618, 231 (2014); 10.1063/1.4897719Flatness-based embedded adaptive fuzzy control of turbocharged diesel engines AIP Conf.Abstract. A nonlinear controller is designed for air-fuel ratio control in combustion engines, making use of differential flatness theory and of the Derivative-free nonlinear Kalman Filter. It is proven that the air-fuel ratio system is a differentially flat one and admits dynamic feedback linearization. Using a change of variables that is based on differential flatness theory it is shown that the air-fuel ratio system can be transformed to the linear canonical form, for which the design of a state feedback controller is easier. Moreover, to compensate for modeling uncertainties and external disturbances the Derivativefree nonlinear Kalman Filter is designed as a disturbance observer. The estimation of the perturbations that effect the air-fuel systems enables their compensation through the inclusion of an additional term in the feedback control law. The efficiency of the proposed nonlinear feedback control scheme is tested through simulation experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

Flatness-based embedded control of air-fuel ratio in combustion engines

Rigatos¹,

Siano²,

Arsie³

2014

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…In terms of advanced approaches, the use of nonlinear feedforward controllers (Guzzella, 1995), adaptive controllers (Ault et al, 1994), (Turin and Geering, 1995), (Jones et al, 1995), (Rupp et al, 2008), (Rupp, 2009), feedback linearization (Guzzella et al, 1997), observer based controllers (Chang et al, 1995), (Powell et al, 1998), , sliding mode controllers (Won et al, 1998), (Pieper and Mehrotra, 1999), (Souder and Hedrick, 2004), linear quadratic regulators (Ohata et al, 1995), (Onder and Geering, 1993), H V controllers (Vigild et al, 1999), (Mianzo et al, 2001), Smith Predictors (Nakagawa et al, 2002), neural network controllers (Zhai and Yu, in press) and model predictive controllers (Muske and Jones, 2006) can be mentioned. The use of an electronic throttle as an additional control actuator (Chang et al, 1993) or secondary/port throttles (Stefanopoulou et al, 1994) has been also explored.…”

Section: Introductionmentioning

confidence: 99%

Spark ignition engine fuel-to-air ratio control: An adaptive control approach

Yıldız

Annaswamy

Yanakiev

et al. 2010

Control Engineering Practice

View full text Add to dashboard Cite

show abstract

“…The feedback linearization approach has been previously applied to the A/F control problem in [5]. Here we employ somewhat different derivation of this controller, and then use the collocation method to determine stability and guaranteed rate of convergence regions as well as LMI techniques to characterize the controller disturbance rejection properties.…”

Section: Feedback Linearization Controller For the Case Of A Slowmentioning

confidence: 99%

Analysis and control of delay-dependent behavior of engine air-to-fuel ratio

Averina

Kolmanovsky²,

Gibson³

et al.

Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005.

View full text Add to dashboard Cite

The paper analyzes the influence of the delay on air-to-fuel ratio (A/F) regulation in internal combustion engines. Two feedback controller architectures, an integral controller for the case of a fast A/F sensor and a feedback linearization controller for the case of a slow A/F sensor, are considered. The collocation method is applied to determine the stability and guaranteed rate of convergence regions (charts) in the space of engine and controller parameters and we demonstrate that these charts can be used to automatically schedule A/F feedback controller gains as functions of engine operating conditions. Linear Matrix Inequality (LMI) techniques are employed for the analysis of disturbance rejection properties of the controllers.

show abstract

Feedback Linearizing Air/Fuel-Ratio Controller

Cited by 3 publications

References 3 publications

Flatness-based embedded control of air-fuel ratio in combustion engines

Flatness-based embedded control of air-fuel ratio in combustion engines

Spark ignition engine fuel-to-air ratio control: An adaptive control approach

Analysis and control of delay-dependent behavior of engine air-to-fuel ratio

Contact Info

Product

Resources

About