In this paper, model sets for continuous–time linear time invariant systems that are spanned by fixed pole orthonormal bases are investigated. These bases generalise the well known Laguerre and two–parameter Kautz cases. It is shown that the obtained model sets are norm dense in the Hardy space H1(Π) under the same condition as previously derived by the authors for the norm denseness in the (Π ...

The establishment of global helicopter linear model is very precious and useful for the design of the linear control laws, since it is never afforded in the published literatures. In the first principle approach, the mathematical model was developed using basic helicopter theory accounting for particular characteristic of the miniature helicopter. No formal system identification procedures are ...

System identification is the art and science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real world of applications and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications. System identification is a very large topic, with different ...

This paper presents insights gained while developing System Requirements Specification of a flight control system within a formal framework. SCR methodology has been used for the description of the requirements of Sensor Failure Detection and Identification Scheme. The emphasis is on the practical aspects and experience gained through the application of a formal method in developing the system ...

Fuzzy model-based adaptive control, unlike traditional fuzzy control, extracts expert knowledge from data by using model identification techniques. In this paper, we propose an analysis of the contradiction in this knowledge as an additional search criterion during the model identification process. In order to do so, we first define a measure of contradiction between fuzzy rules. Then, we assum...

Fuzzy model-based adaptive control, unlike traditional fuzzy control, extracts expert knowledge from data by using model identification techniques. In this paper, we propose an analysis of the contradiction in this knowledge as an additional search criterion during the model identification process. In order to do so, we first define a measure of contradiction between fuzzy rules. Then, we assum...

smart home is composed of several controllers with different plants in control. if each controller works independently, without considering the mutual effect of the others in the control process, the whole system could definitely not converge to an optimum desired status and may not ever reach the demanded condition. the function of different controller system may has conflict in some condition...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

the purpose of this study was to estimate the torque from high‑density surface electromyography signals of biceps brachii, brachioradialis, and the medial and lateral heads of triceps brachii muscles during moderate‑to‑high isometric elbow flexion‑extension. the elbow torque was estimated in two following steps: first, surface electromyography (emg) amplitudes were estimated using principal com...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...