DEVELOPING GREY-BOX DYNAMIC PROCESS MODELS
نویسندگان
چکیده
منابع مشابه
Real-time Process Optimization Based on Grey-box Neural Models
This paper investigates the feasibility of using grey-box neural models (GNM) in Real Time Optimization (RTO). These models are based on a suitable combination of fundamental conservation laws and neural networks, being used in at least two different ways: to complement available phenomenological knowledge with empirical information, or to reduce dimensionality of complex rigorous physical mode...
متن کاملParameter estimation in stochastic grey-box models
An e2cient and 3exible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Itô stochastic di6erential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended Kalman 9lter and features maximum likelihood as well as maximum a posteriori estimation on multiple indepen...
متن کاملGrey-Box Control Oriented Emissions Models
Further improvements of emission control will require reliable estimation of emissions in real time. While many progresses are being done in terms of physical sensors, there is a wide agreement that virtual sensors and more in general real time emission models will play a central role in the next steps. While there is a deep understanding of the physics of the regulated pollutants, most general...
متن کاملGrey-Box Checking
There are many cases where we want to verify a system that does not have a usable formal model: the model may be missing, out of date, or simply too big to be used. A possible method is to analyze the system while learning the model (black box checking). However, learning may be an expensive task, thus it needs to be guided, e.g., using the checked property or an inaccurate model (adaptive mode...
متن کاملA method for systematic improvement of stochastic grey-box models
A systematic framework for improving the quality of continuous time models of dynamic systems based on experimental data is presented. The framework is based on an interplay between stochastic differential equation modelling, statistical tests and nonparametric modelling and provides features that allow model deficiencies to be pinpointed and their structural origin to be uncovered. More specif...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2018
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2018.03.088