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The main goal of this project was to use the Modelica features on embedded systems, real-time systems and basic mechanical modeling for the control of a two-wheeled self-balancing personal vehicle. The Elektor Wheelie, a Segway-like vehicle, was selected as the process to control. Modelica is an object-oriented language aimed at modeling of complex systems. The work in the thesis used the Modelica

The Kalix River, located in the northern part of Sweden, experiences a slowdown in water flow during cold winters. However, in spring, when snow and ice melt in the mountains, the water flow starts to increase. Towards the end of spring, there is usually a rapid and unpredictable surge in water flow known as the spring flood. The arrival of the spring flood is stochastic in time and does not occur

We derive a sequential algorithm for simultaneous calibration and quadratic hedging of options. It can be applied to any model from which we can simulate paths and price options. The quadratic hedging comes at no extra cost! We have calibrated the Bates and NIG-CIR model to S&P 500 index options in order to evaluate various hedging strategies (delta, quadratic), clearly indicating the advantag

Popular Abstract in Swedish Under de senaste decennierna har matematisk modellering av finansiella marknader rönt stor uppmärksamhet både inom akademi och inom industri. Ett område som har visats särskilt intresse är prissättning av finansiella instrument så som optioner. En europeisk köpoption på en underliggande aktie är ett kontrakt som ger innehavaren rätten att vid en förutbestämt tidpunkt, The first part of this thesis deals with approximations of stochastic integrals and discrete time hedging of derivative contracts; two closely related subjects. Paper A considers the problem of approximating the value of a Wiener process. The discretization points are placed at times when the absolute difference between the value of the process and the approximation reaches a threshold level. It i

1. State space models are starting to replace more simple time series models in analyses of temporal dynamics of populations that are not perfectly censused. By simultaneously modelling both the dynamics and the observations, consistent estimates of population dynamical parameters may be obtained. For many data sets, the distribution of observation errors is unknown and error models typically chos

The land surface temperature (LT) is a crucial variable that governs the energy and radiation budget of the earth's atmosphere and influences land-atmosphere interactions. The LT plays a crucial role mainly in the short-range forecast of a numerical weather prediction (NWP) model. The primary research goal in this research work undertaken is to assess the impact of assimilation of LT data from the

To estimate the long memory series in the framework of state space model is rarely documented although the theoretical foundation was well built in late 90s, and the literatures concentrate mainly on the estimation in stationary case. This paper aims to estimate the parameters in a wide range of long memory series by applying approximate Maximum Likelihood Estimation (MLE) and Bayesian Monte Carlo

Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applicationsin e.g networked control systems (NCS). However, the problem of designing an optimal event-based state estimator often becomes untractable due to nonlinear measurements. This complexity is avoided with stochastic event-triggering. In this work, we

In order to improve the security of the vehicles, the car industry focuses more and more on Active Safety. The objective is to introduce embedded electronic control systems to detect dangerous conditions, warn the driver and, in emergency situations, even take actions to avoid crash or at least reduce the violence of the impact. The tire-road friction coefficient which defines the maximum traction

The permanent magnet synchronous motor, PMSM, is an efficient electrical motor that has seen a greater prevalence in the automotive industry from the increasing demand for electrical vehicles. Managing the temperature of the permanent magnet rotor is important to optimize motor utilization and avoid hardware failures. Direct temperature measurements of the moving rotor with a sensor are, however,

Iii analysis-by-synthesis linear predictive coding (AbS-LPC) an LPC synthesis filter is combined with an analysis-by-synthesis search of the excitation signal. The synthesis filter is an estimator for the speech signal given the excitation. However in most AbS-LPC algorithms this estimator has no explicit model of the quantization noise, which is present in the excitation signal. This paper descri

When treating patients suffering from renal failure with hemodialysis, an obvious point of interest is the actual blood cleaning efficiency of the dialyzer (artificial kidney). This efficiency is called clearance or dialysance. The method currently used for estimating clearance is based on doing a step-change on the process. Due to the nature of the process, this method is slow and has a relativel