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Decentralized Estimation Using Conservative Information Extraction
Sensor networks consist of sensors (e.g., radar and cameras) and processing units (e.g., estimators), where in the former information extraction occurs and in the latter estimates are formed. In decentralized estimation information extracted by sensors has been pre-processed at an intermediate processing unit prior to arriving at an estimator. Pre-processing of information allows for the complexity of large systems and systems-of-systems to be significantly reduced, and also makes the sensor network robust and flexible. One of the main disadvantages of pre-processing information is that information becomes correlated. These correlations, if not handled carefully, potentially lead to underest...
Uncertainties in Neural Networks
In science, technology, and engineering, creating models of the environment to predict future events has always been a key component. The models could be everything from how the friction of a tire depends on the wheels slip to how a pathogen is spread throughout society. As more data becomes available, the use of data-driven black-box models becomes more attractive. In many areas they have shown promising results, but for them to be used widespread in safety-critical applications such as autonomous driving some notion of uncertainty in the prediction is required. An example of such a black-box model is neural networks (NNs). This thesis aims to increase the usefulness of NNs by presenting an...
Some results on closed-loop identification of quadcopters
In recent years, the quadcopter has become a popular platform both in research activities and in industrial development. Its success is due to its increased performance and capabilities, where modeling and control synthesis play essential roles. These techniques have been used for stabilizing the quadcopter in different flight conditions such as hovering and climbing. The performance of the control system depends on parameters of the quadcopter which are often unknown and need to be estimated. The common approach to determine such parameters is to rely on accurate measurements from external sources, i.e., a motion capture system. In this work, only measurements from low-cost onboard sensors ...
On Motion Planning Using Numerical Optimal Control
During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. In this thesis, the objective is not only to find feasible solutions to a motion planning problem, but solutions that also optimize some kind of performance measure. From a control perspective, the resulting problem is an instance of an optimal control problem. In this thesis, the focus is to further develop optimal control algorithms such that they be can used to obtain improved solutions to motion planning problems. This is achieved by combi...
Sensor Management for Target Tracking Applications
Many practical applications, such as search and rescue operations and environmental monitoring, involve the use of mobile sensor platforms. The workload of the sensor operators is becoming overwhelming, as both the number of sensors and their complexity are increasing. This thesis addresses the problem of automating sensor systems to support the operators. This is often referred to as sensor management. By planning trajectories for the sensor platforms and exploiting sensor characteristics, the accuracy of the resulting state estimates can be improved. The considered sensor management problems are formulated in the framework of stochastic optimal control, where prior knowledge, sensor models...
On Complexity Certification of Active-Set QP Methods with Applications to Linear MPC
In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these efficiently and to have good upper bounds on worst-case solution time. Often for linear MPC problems, the optimization problem in question is a quadratic program (QP) that depends on parameters such as system states and reference signals. A popular class of methods for solving such QPs is active-set methods, where a sequence of linear systems of equations is solved. The primary contribution of this thesis is a method which determines which sequence of subproblems a popular class of such active-set algorithms need to solve, for every p...
Reglerteknik
Denna bok introducerar ämnet reglerteknik på ett modernt sätt. Den är lämplig som litteratur för en grundkurs i reglerteknik på civilingenjörsprogram. Den täcker traditionella metoder baserade på - Laplacetransformen - Tillståndsbeskrivningar - Frekvensbeskrivningar I början av boken ligger fokus på enkla designmetoder som lambdainställning av PID-regulatorer och andra regulatorer med en intern modell. Möjligheter och begränsningar för dessa metoder diskuteras i detalj. Mer avancerade designmetoder baserade på polplacering, tillståndsåterkoppling, och rekonstruktion av tillstånd samt kompensering i frekvensplanet diskuteras också ingående i senare delar i boken. Boken ...
Days of Burning, Days of Wrath
A NEW NOVEL IN TOM KRATMAN'S HARD-HITTING MILITARY SF CARRERA SERIES When Patricio Carrera’s family was murdered by Salafist terrorists aided and abetted by the fleet of alien Earth, the only restraint on his ruthlessness and ambition was also removed. Now, after decades of war and preparation for war in his adopted homeland of Balboa, the last of the Tauran Union Expeditionary Force collapses and is herded into prison camps and ships, where their re-education commences. An Islamic rebellion explodes inside the Tauran Union, bringing the governments and the bureaucracies to their knees . . . except when they’re hauled up by their necks on lampposts. In neighboring Santa Josefina, the Tau...
