Non-linear system identi®cation using closed-loop data with no external excitation: the case of a lean combustion chamber
نویسندگان
چکیده
This paper deals with the analysis of a set of measurements collected on a lean premixed combustion process operating in a limit cycle. Due to the fact that the data are collected in closed-loop and the system has no external excitation, the identi®cation task is particularly challenging. This work mainly focuses on the issue of the feasibility of the identi®cation task. It will be shown that, despite the paucity of information available, a grey-box non-linear model can be estimated. The model provides an explanation both of the limit-cycle fundamental oscillation and of a non-harmonic high-frequency signal a ecting the pressure of the combustion chamber.
منابع مشابه
SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS
In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...
متن کاملExperimental investigations on a pre-chamber spark plug with variable heat range by integrating a controlled hot surface
In gasoline engines, pre-chamber spark ignition systems are used to achieve high efficiency and low NOx emissions when operating under lean conditions. While a cold pre-chamber spark plug can lead to misfiring and flame quenching under cold start or part load operation, a hot pre-chamber can result in uncontrolled pre-ignition phenomena under full load operation. This paper presents an approach...
متن کاملAdaptive fuzzy pole placement for stabilization of non-linear systems
A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...
متن کاملA closed � loop system identi cation toolbox for Matlab zx
A closed loop system identi cation toolbox for Matlab is presented includ ing a user friendly graphical user interface that communicates with MathWork s System Identi cation Toolbox SITB version With the CLOSID toolbox it is possible to identify linear parametric models on the basis of experimental data obtained from a plant that is operating under the presence of a controller The toolbox is de...
متن کاملProperties and Usage of Closed-loop Identiication Methods Properties and Usage of Closed-loop Identiication Methods
System identi cation deals with the construction of mathematical models of dynamical systems using measured data. Closed-loop identi cation is what results when performing the identi cation experiment under output feedback, that is, in closed loop. In this thesis we study a number of closed-loop identi cation methods, both classical and more recently suggested ones. A common feature of the meth...
متن کامل