Nonlinear Parametric Model Identification with Genetic Algorithms. Application to a Thermal Process

نویسندگان

  • Xavier Blasco Ferragud
  • Juan Manuel Herrero Durá
  • Miguel Andres Martínez Iranzo
  • Juan S. Senent Español
چکیده

One of the first steps taken in any technological area is building a mathematical model. In fact, in the case of process control, modelling is a crucial aspect that influences quality control. Building a nonlinear model is a traditional problem. This paper illustrates how to built an accurate nonlinear model combining first principle modelling and a parametric identification, using Genetic Algorithms. All the experiments presented in this paper are designed for a thermal process.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Nonlinear Parametric Identification of an IPMC Actuator Model

Ionic polymer metal composite is a class of electro-active polymers which are very attractive smart actuators due to its large bending deflection, high mechanical flexibility, low excitation voltage, low density, and ease of fabrication. These properties make IPMC a proper candidate for many applications in various fields such as robotics, aerospace, biomedicine, etc. Although the actuation beh...

متن کامل

Solving a Stochastic Cellular Manufacturing Model by Using Genetic Algorithms

This paper presents a mathematical model for designing cellular manufacturing systems (CMSs) solved by genetic algorithms. This model assumes a dynamic production, a stochastic demand, routing flexibility, and machine flexibility. CMS is an application of group technology (GT) for clustering parts and machines by means of their operational and / or apparent form similarity in different aspects ...

متن کامل

Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms

Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

متن کامل

Functional-Coefficient Autoregressive Model and its Application for Prediction of the Iranian Heavy Crude Oil Price

Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...

متن کامل

Nonlinear Robust Identification with −GA: FPS Under Several Norms Simultaneously

In nonlinear robust identification context, a process model is represented by a nominal model and possible deviations. With parametric models this process model can be expressed as the so-called Feasible Parameter Set (FPS), which derives from the minimization of identification error specific norms. In this work, several norms are used simultaneously to obtain the FPS. This fact improves the mo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001