<p>Today small metal parts are mass-produced as for example rollers in cylinder bearings. At high velocity cutting the metal is cut with a great force in a scissor-like device. Both precision and repeatability is important to be able to guarantee good quality, but from an economical point of view it is also important to keep a great manufacturing capacity. The part of the process that is most time consuming is when the metal bar, that is about to be cut, is fed to the right position. Therefore it is interesting to examine if the time used for positioning can be reduced. This thesis examines if more advanced automatic control can be used to speed up the process while maintaining the precision. In order to test and evaluate different theories, two different mathematical models have been developed. The models where implemented in the simulation program SIMULINK in MATLAB and they where compared to and adapted to data measured on the physical machine. One model is developed from physical relationships and mostly used for simulations while the other one, a condition state model, has been used for regulator design. The first question to answer was if it is at all possible to control the process any faster. When a theoretical limit was found the next step was to design a regulator to show that the theory of automatic control does not imply too great limitations. The design that was chosen was condition state feedback where the states were appraised with an observer. </p><p>A faster system will raise the demands on cycle times and precision. To make sure that the hardware isn’t the limiting factor, design requirements have been set up. A small list of what hardware is available has also been put together (and shows that it is possible to implement such a system). </p><p>The conclusion is that it is, theoretically, possible to radically increase the manufacturing capacity. The assumptions for this to be accomplished is especially that the uncertainty of the model is minimizedand that hardware with enough capacity can be found.</p>

<p>Modern missiles must meet higher and higher demands. They should be autonomous, have long range and still have a big effect on the target. To maximize effect on target some missiles not only minimize miss distance, but also try to hit with a certain angle; often perpendicular to the surface of the target. </p><p>In this thesis a method to guide the missile in the terminal phase of its mission where both point of impact as angle of impact are specified. The method consist of two parts. First a reference trajectory with best possible impact conditions, considering the performance of the missile, is computed. The second part consist of a guidance law which guide the missile along the reference trajectory to the target. Two laws were tested, Biased Proportional Navigation (BPN) and Modified Biased Proportional Navigation (MBPN). </p><p>The method was implemented in an existing detailed simulation system. A big number of simulations were done to optimize the algorithms, and to evaluate performance. </p><p>Performance was then compared to an already existing method for terminal guidance. The new method was better in terms of angle of impact but worse considering point of impact. One big advantage with the new method is that after calculation of the reference trajectory but before the actual flight (to target) it is possible to predict, with a high level of certainty, if the missile is going to hit the target or not.</p>

This master's thesis presents the development of a collision handling function for Motoman industrial robots and investigates further use of the developed software. When a collision occurs the arm is to be retracted to a safe home location and the job is to be restarted to resume the production. The retraction can be done manually, which demands that the operator has to have good knowledge in robot handling and it might be a time consuming task. To minimise the time for restarting the job after a collision and allowing employees that have limited knowledge in robot handling to retract and restart the job, Motoman provides an automatical retraction function. However, the retraction function may cause further collisions when used and therefor a new function for retracting the arm is needed. The new function is based on that the motion of the robot is recorded by sampling the servo values, which are then stored in a buffer. A job file is automatically created and loaded into the control system, and the position variables of the job file are updated using the contents of the buffer. This will ensure a safe retraction of the arm as long as the environment surrounding the robot remains the same. The developed software made it possible to control the robot in real-time by changing the buffer information, which has lead to a cognitive system called the Pathfinder. By initiating the Pathfinder function with at least a start and an end point, the function generates a collision free path between the start point and the end point. A pilot-study has also been made concerning integration of a vision system with the Pathfinder to increase the decision handling for the function.

In this thesis, we address a number of challenges in cluster analysis. We begin by investigating one of the oldest and most challenging problems: determining the number of clusters, k. For this problem, we propose a novel solution that, unlike previous techniques, delivers both the number of clusters and the clusters in one-shot (in contrast, conventional techniques run a given clustering algorithm several times for different values of k, and/or for several initialization with the same k). The second challenge we treat is the drawback, briefly mentioned above, of many conventional iterative clustering algorithms: how should they be initialized? We propose an initialization scheme that is applicable to multiple iterative clustering techniques that are widely used in practice (e.g., spectral clustering, EM-based, k-means). Numerical simulations demonstrate a significant improvement compared to many state-of-the-art initialization techniques. Third, we consider the computation of pairwise similarities between datapoints. A matrix of such similarities (the similarity matrix) constitutes the backbone of many clustering as well as unsupervised learning algorithms. In particular, for a given similarity metric, we propose a similarity transformation that promotes high similarity between the points within the cluster and deceases the similarity within the cluster overlapping regions. The transformation is particularly well-suited for many clustering and dimensionality reduction techniques, which we demonstrate in extensive numerical experiments. Finally, we investigate the application of clustering algorithms to image and video datasets (also known as superpixel segmentation). We propose a segmentation algorithm that significantly outperforms current state-of-the-art algorithms; both in terms of runtime as well as standard accuracy metrics. Based on this algorithm, we develop a tool for fast and accurate image annotation. Our findings show that our annotation technique accelerates the annotation processes by up to 20 times, without compromising the quality. This indicates a big opportunity to significantly speed up all AI computer vision tasks, since image annotation forms a crucial step in creating training data. / Den här avhandlingen behandlar en rad utmaningar inom klusteranalys. Till att börja med undersöker vi ett av de äldsta och mest utmanande problemen: att bestämma antalet kluster k utifrån data. Vi föreslår en ny algoritm som, till skillnad från tidigare algoritmer, ger antalet kluster (samt själva klustren) från enbart en körning. (Tidigare algoritmer kräver att dessa algoritmer körs flera gånger för olika värden på k, eller från olika startpunkter för samma värde på k.) Den andra utmaningen vi behandlar är hur de idag vanligast förekommande klusteringsalgoritmerna (e.g., spektral-, EM-baserad-, samt k-means-klustering) bör initialiseras. Vi föreslår en initialiseringsmetod, och demonstrerar i numeriska simulationer att denna ger signifikant bättre resultat jämfört med de nuvarande bästa metoderna. Som tredje del i avhandlingen studerar vi konstruktionen av mått på parvis likhet mellan datapunkter. En matris bestående av sådana likheter ligger till grund för många klusteringsalgoritmer, samt metoder för oövervakad inlärning inom maskininlärning. Mer specifikt så demonstrerar vi hur en likhetstransformation kan tillämpas på ett givet likhetsmått för att främja likhet mellan datapunkter inom samma kluster och undertrycka likhet för punkter som ligger i områden där kluster överlappar. Transformationen vi föreslår är speciellt lämpad för klusterings- och dimensionsreduceringsalgoritmer, vilket vi demonstrerar i omfattande numeriska experiment. Till sist studerar vi tillämpningar av klusteringsalgoritmer på bild- och videodata. Vi föreslår en segmenteringsalgoritm med signifikant bättre prestanda än de nuvarande bästa algoritmerna; både i termer av beräkningskomplexitet samt precision. Vidare så utvecklar vi en mjukvara baserad på vår algoritm för snabb och precis bildsegmentering. Våra studier visar att bildsegmentering och -annotering kan utföras upp till 20 gånger snabbare än med nuvarande mjukvaror, utan att vi kompromissar på kvalit´en. Detta pekar mot stora möjligheter att snabba upp många applikationer inom datorseende, eftersom segmenterad bilddata ligger till grund som träningsdata för många algoritmer.

Lic.-avh. Linköping : Linköpings universitet, 2005.

Currently the housing sector accounts for about 40 percent of societies total energy consumption. New methods of constructing houses can greatly reduce the use of energy for modern homes but measures must also be taken to make existing buildings more energy effective. One method of doing so is by so called weather optimization of the buildings heating system. This means that the level of heating is based on detailed information about the weather instead of solely the temperature, which is the case for the majority of buildings today.  The aim of this report is to evaluate these systems from a real estate owner perspective. This is done by studying a commercially available system and a locally developed system for weather optimization in order to evaluate how they operate, their benefits and the level of competence needed to implement them.

In order to control a system or process a PID-regulator is often used although they can be difficult to tune so that they give the system a preferred behaviour. The goal with this project is to tune a PID-controller that controls the temperature of a large water tank. The initial systems temperature fluctuates around the set temperature by +/- 1◦C and our goal is to reduce it to +/- 0.5◦C. The project will use the parametric method of a step response in order to evaluate the systems behaviour into a transfer function model that can be PID-tuned. The system was modeled into a a first order model that matches the heating and cooling separately although not together since they have different time constants. Therefore a second order model was made. This model did not match the collected data very good but is used to get a better understanding of the system and figure out what kind of parameters that are required in order to create a better matching model. The final conclusion is that in order to get a matching transfer function of the plant a second order model or higher must be uses and also that more data distributed along more parameters need to be logged in order to understand the entire system behaviour.

Boliden Aitik is the largest open-pit copper mine in Sweden, and during 2017, more than 39 million tonnes of ore was processed into concentrated copper, silver and gold. The distributed control system 800xA is provided by ABB, and this is what the operators use for process monitoring and control. Currently, the control of the mill discharge pumps operating to transport slurry from the mill circuit to the flotation system is not completely satisfactory. This leads to additional work for the operators, and can in worst case interfere with production.  This project has aimed to identify the problems with the existing control solution mainly from the operators and the engineers perspective, but also by looking at trend data. The discharge pump system has also been modeled, based on a combination of theoretical knowledge and real sensor data obtained from the process control system. The model has been implemented in a 800xA simulation environment, where alternative control solutions have been simulated and evaluated. The modeling procedure has been limited by the lack of pressure, density and flow sensors in slurry flows, and this has lead to an increased uncertainty, in particular for the dynamic characteristics of the pump system. The static characteristics of the discharge pumps have been modeled by regression analysis of a large amount of steady state data over several months, and the dynamic characteristics have been identified from a step response experiment. A cascade connection of proportional-integral (PI) controllers are used for pump control, where the primary controller uses parameter scheduling as a function of measured tank level. This leads to smooth control during normal mill circuit operation, which is a benefit for the flotation process, but it can also cause problems such as flooding, in particular at mill circuit starts or when switching between pumps. According to simulations, it seems like some modifications in the PI control should make it possible to use smooth control around the reference level, and to still avoid flooding at the situations that appear to be problematic today. The initial goal of this project was a live implementation of improved control, but this was not possible during the final weeks of this project. Instead, the simulation results should be used as support for future decision making and controller tuning.

Modelling a linear mathematical model of a radio controlled (RC) helicopter in hover is the main goal of this thesis. The thesis introduces a general description about how RC-helicopters work and different phenomenons that effect the behaviour of a RC-helicopter. These phenomenons play an important role in the modelling part. The model equations of the RC-helicopter are computed by deriving mathematical descriptions of different helicopter characteristics. The flapping motion of the main rotor and the flybar are modelled since they play major role in describing helicopter dynamics. The model is linearised by using stability and control derivatives and a model structure is presented. The method describes how the external forces and moments in the rigid body equations of motion can be expressed as continuous functions of the model states and inputs. The model is divided into multiple sub-models that describe the different dynamics of the RUAV. The prarameters of the model are estimated using system identification methods. The prediction error method proved itself successful and the achieved models can accurately estimate the pitch, roll and yaw rate of the helicopter. These models could be used for further development of control designs.

The aim of this Licentiate is to advance the field of cooperative visual coverage path planners for multiple Micro Aerial Vehicles (MAVs), while aiming for their real life adoption towards the tasks of aerial infrastructure inspection. The fields that will be addressed are focusing in: a) the collaborative perception of the environment, b) the collaborative visual inspection, and c) the optimization of the aerial missions based on the remaining flying battery, camera constraints, coverage constraints and other real life mission induced constraints. Towards this envisioned aim, this Licentiate will present the following main theoretical contributions: a) centralized and distributed Model Predictive Control (MPC) schemes for the cooperative motion control of MAVs focusing in the establishing of a formation control architecture to enable a dynamic visual sensor from monocular cameras towards a reconfigurable environmental perception, b) revisiting the Cooperative Coverage Path Planning (C-CPP) problem for the inspection of complex infrastructures, c) developing a holistic approach to the problems of 2-D area coverage with MAVs for polygon areas, while considering the camera footprint, and d) designing of a scheme to estimate the Remaining Useful Life (RUL) of the battery during a flight mission, a fact that directly effects the flying capabilities of the MAVs. The theoretical contributions of this thesis have been extensively evaluated in simulation and real life large scale field trials, a direction that adds another contribution of the suggested framework towards the massive insertion of the aerial platforms as aerial tools in the close future. In the first part of this Licentiate, the vision, motivation, open challenges, contributions, and future works are discussed, while in the second part the full articles connected to the presented contributions in this Licentiate are presented in the annex.