In thia paper we investigate some important iasuer in system identification for the windsvrier approsch to robust adaptive control. In particular, correlation function estimates and power spectrum estimates are compared as methods for model validation. This comparison leads us to suggest a reliable procedure for deciding (1) when should we identify a better model, and (2) whether we have identi...

A commonly occurring control problem in the chemical process industries is the control of fluid levels in storage tanks, chemical blending and reaction vessels. In this paper we are addressing model identification of simple coupled two tanks, which are coupled by a valve. We have found practically the model by using MATLAB environment, which gives results almost identical to ideal model of plan...

The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering unmodeled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but...

This study aims at integrating system identification for robust control with process control. We consider linear systems where the parameters normally vary slowly, but which may exhibit sudden and large changes. One example of such a system is an extruder where the parameters vary slowly e.g. due to temperature changes, and where the die sometimes is changed, leading to sudden and large changes...

Abstract The volume of data processed by the Large Hadron Collider experiments demands sophisticated selection rules typically based on machine learning algorithms. One shortcomings these approaches is their profound sensitivity to biases in training samples. In case particle identification (PID), this might lead degradation efficiency for some decays not present dataset due differences input k...