Abstract

In this paper, the problem of trajectory tracking control in an inertia wheel pendulum is studied. Results are presented in a constructive form. First, a model-based controller is obtained by using the output feedback linearization technique. Then, the controller is redesigned by [...]

Abstract

A neural network noise prediction model for a turbulent boundary layer noise mechanism has been created using a feed forward multilayer perceptron and a noise spectrum database collected from a family of NACA 0012 areofoils. The results of the neural network model were compared [...]

Abstract

Quantitative investment is the process of establishing mathematical models using statistics, information technology, and mathematics to quantify and implement risks, returns, and traditional investment concepts. However, due to the backwardness of computing tools in the past, quantitative [...]

Abstract

Traffic congestion is a severe problem in urban areas and it leads to the emission of greenhouse gases and air pollution. In general, drivers lack knowledge of the location and availability of free parking spaces in urban cities. This leads to people driving around searching for parking [...]

Abstract

Prediction of human driving decisions is an important aspect of modeling human behavior for the application to Advanced Driver Assistance Systems (ADAS) in the intelligent vehicles. This paper presents a sensor based receding horizon model for the prediction of human driving commands. [...]

Abstract

Industrial pipelines must be inspected to detect typical failures, such as obstructions and deformations, during their lifetime. In the petroleum industry, the most used non-destructive technique to inspect buried pipelines is pigging. This technique consists of launching a Pipeline [...]

Abstract

International audience; 4D trajectory prediction is the core element of future air transportation system, which is intended to improve the operational ability and the predictability of air traffic. In this paper, we introduce a novel model to address the short-term trajectory prediction [...]

Abstract

The creation of surrogate models is a classical problem in Machine Learning. The present paper is a case study of training a surrogate model for a real-life engineering problem: the computation of the sag of a cable hanging between two pylons. Neural networks have been trained using [...]

Abstract

A novel approach is presented for efficiently training a neural network (NN)-based surrogate model when the training data set is to be generated using a computationally intensive high-fidelity computational model. The approach consists in using a Gaussian Process (GP), and more specifically, [...]

Abstract

The estimation of the Angle of Attack (AOA) and Angle of Sideslip (AOS) is crucial for flight monitoring and control. However, a gap has been identified on the data selection technique for the class of estimators based on data-driven methods, such as the synthetic sensor based on [...]