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The effect of anesthetics in the human body is usually described by Wiener models. The high number of patient-dependent parameters in the standard models, the poor excitatory pattern of the input signals (administered anesthetics) and the small amount of available input-output data make application of system identification strategies difficult. The idea behind this thesis is that, by reducing the number of parameters to describe the system, improved results may be achieved when system identification algorithms and control strategies based on those models are designed. The choice of the appropriate number of parameters matches the parsimony principle of system identification. The three first papers in this thesis present Wiener models with a reduced number of parameters for the neuromuscular blockade and the depth of anesthesia. Batch and recursive system identification algorithms are presented. Taking advantage of the small number of continuous time model parameters, adaptive controllers are proposed in the two last papers. The controller structure combines an inversion of the static nonlinearity of the Wiener model with a linear controller for the exactly linearized system, using the parameter estimates obtained recursively by an extended Kalman filter. The performance of the adaptive nonlinear controllers is tested in a database of realistic patients with good results.

The stringent regulations on the emissions levels of heavy duty vehicles create a demand for new methods of reducing harmful emissions from the engine. In order to be able to follow these increasingly stricter legislations, complex aftertreatment systems are used. Achievement of optimal performance of these systems requires accurate models that can be used for control design. As a result, the interest in modelling and control of aftertreatment systems has increased. This thesis deals with the modelling of the nitrogen oxide (NOx) emissions from heavy duty vehicles using the selective catalyst as an aftertreatment system for its reduction. The process of the selective catalytic reduction (SCR) is nonlinear since the chemical reactions involved are highly depending on the operating point. The momentary operating point is defined by the driving profile of the vehicle which, for example, includes cold and hot engine starts, highway and urban driving. The purpose of this thesis is to investigate different methods for nonlinear system identification of SCR systems with control in mind. The first two papers contain the theoretical work of this thesis. The first paper deals with improvement of an existing recursive prediction error method (RPEM) where a more accurate discretisation algorithm was used to improve the accuracy of the estimated nonlinear model. The second paper deals with analysis of the convergence properties of the algorithm. For this analysis several conditions were formulated that link the global and local convergence properties of the algorithm to stability properties of an associated differential equation. Global convergence to a stationary point was shown. In the third paper, the RPEM is used for identification of the SCR system and finally the fourth paper a Hammerstein–Wiener model for identification of the SCR system is applied. In both these cases the black-box models could predict the NOx behaviour of the SCR system quite well. The nonlinear models were shown to describe the SCR system more accurately than linear models.

Nonlinear system identification methods is a topic that has been gaining interest over the last years. One reason is the many application areas in controller design and system development. However, the problem of modeling nonlinear systems is complex and finding a general method that can be used for many different applications is difficult. This thesis treats recursive identification methods for identification of systems that can be described by nonlinear ordinary differential equations. The general model structure enables application to a wide range of processes. It is also suitable for usage in combination with many nonlinear controller design methods. The first two papers of the thesis illustrates how a recursive prediction error method (RPEM) can be used for identification of an anaerobic digestion process and a solar heating system. In the former case the model complexity is significantly reduced compared to a semi-physical model of the system, without loosing much in model performance. In the latter case it is shown that it is possible to reach convergence even for a small data set, and that the resulting model is of comparable quality as a previously published grey-box model of the same system. The third paper consists of a convergence analysis of the studied RPEM. The analysis exploits averaging analysis using an associated ordinary differential equation, and formulates conditions for convergence to a minimum of the criterion function. Convergence to a true parameter set is also illustrated by an example. The fourth, and last, paper of this thesis addresses the problem of finding suitable initial parameters e.g. for the RPEM. With a potentially non-convex criterion function the choice of initial parameters becomes decisive for whether the algorithm converges to the global optimum, or a local one. The suggested initialization algorithm is a Kalman filter based method. Experiments using a simulated example show that the Kalman based method can, under beneficial circumstances, be used for initialization of the RPEM. The result is further supported by successful identification experiments of a laboratory scale cascaded tanks process, where the Kalman based method was used for initialization.

The rapidly increasing amounts of space debris orbiting Earth is threatening to reach a critical level, where the near-Earth environment becomes so overfilled with junk that many missions simply become unfeasible. Long-term active debris removal operations appear to be a necessity, but due to the scale of the problem this will likely be an expensive affair spanning decades or even centuries. Many of the mission-related costs can be significantly reduced by making use of a smaller spacecraft, such as the rapidly developing CubeSat standard. An issue with this approach is the limited actuation capabilities, as that makes it very difficult to perform orbital maneuvers in a fuel-efficient manner. Rather than making a few high-impulse thrusts over the course of the mission, the thrust must be applied continuously for several hundred hours. This thesis attempts to solve the problem by using a non-linear Model Predictive Control strategy to implement an Orbital and Attitude Control system for a small satellite. This was done in MATLAB, using the fast-NMPC package MATMPC recently developed by Yutao Chen at Padova University. The controller was tested in a realistic model of the near-Earth environment, where disturbances such as drag and gravitational perturbations are simulated. It was shown through simulations that this method can successfully be used to perform a fuel-efficient rendezvous maneuver with an uncontrollable object, a critical step in any Active Debris Removal operation. Using a 4 kg CubeSat with a 30 µN thruster mounted on each of its six surfaces, the total mass consumption for a phasing maneuver of 10 degrees at 300 km altitude was less than 0.1% of the spacecraft mass. This assumes an Isp of 1,150 s, which is the specific impulse of the S-iEPS Electrostatic thruster flown on the Aero-Cube-8 IMPACT mission. This is made possible through prediction horizons spanning several days, which in turn forces the controller to operate at sampling rates as low as 1/100 Hz due to the computational load. Fully realizing the potential of this technique would likely require the inclusion of a low-level controller that uses the generated trajectories as input values, as this would negate many of the issues associated with a heavy computational load. The urgency of the space debris problem, and the endless list of other CubeSat applications that would benefit from a flexible and fuel-efficient AOCS, makes this an interesting to topic to consider for further research.

Energy efficient control of server rooms in modern data centers can help reducing the energy usage of this fast growing industry. Efficient control, however, cannot be achieved without: i) continuously monitoring in real-time the behaviour of the basic thermal nodes within these infras- tructures, i.e., the servers; ii) analyzing the acquired data to model the thermal dynamics within the data center. Accurate data and accurate models are indeed instrumental for implementing efficient data centers cooling strategies. In this thesis we focus on Open Compute Servers, a class of servers designed in an open-source fashion and used by big players like Facebook. We thus propose a set of appropriate methods for collecting real-time data from these platforms and a dedicated thermal model describing the thermal dynamics of the CPUs and RAMs of these servers as a function of both controllable and non-controllable inputs (e.g., the CPU utilization levels and the air mass flow of the server’s fans). We also identify this model from real data and provide the results so to be reusable by other researchers.

Poorly operating control loops cause loss in productivity in almost every industry worldwide. Therefore performance monitoring has been an active area of research for the past decades. In this work, a newly developed fault detection method is applied to the monitoring of lambda-tuned control loops. The lambda-tuning method has, due to its simple use, become very popular in the pulp and paper industry and is now spreading to other industries. A model-based fault detection algorithm assuming uncertain process parameters is used for detecting changes in the process. The algorithm consists of two parts, a residual and a time-varying threshold. The a priori information obtained from lambda-tuning is used to create an observer, which is used as residual generator. Known process inputs are used together with upper bounds for the uncertainties and upper bounds for disturbances when calculating the detection threshold. The observer may have integral action in order to make the threshold tight to the residual. Upper bounds for the uncertainties in the process parameters and upper bounds for disturbances are tuning parameters in the algorithm. Two different methods for finding those parameter values are proposed. The first is an approach based on allowed loss in phase margin and the second consists of solving a nonlinear optimization problem to minimize the difference between the residual and the threshold. The algorithm is tested in a simple water tank system. The threshold handles step changes in reference value without giving any false alarms. A fault is introduced by widening of the output in the water tank which simulates a change in the process parameters. The residual then gets larger than the threshold and the fault is detected. / <p>Godkänd; 2006; 20061120 (pafi)</p>

This work is about interaction. Research in the field of information visualization has traditionally been slanted more towards presentation; this even though humans are interactive creatures. We observe our surroundings, make decisions based on what we see and react back into the world. It may all have had its modest beginnings on the primordial Xerox Parc desktop but user interfaces of today are becoming more and more faithful representations of our everyday environments. Between the promise of augmented reality and ubiquitous computing, who knows where we are headed. One thing is certain however; whatever world we end up in, we will continue to interact with visual devices. Three papers make up this thesis: Three-dimensional user interfaces are often considered worse than two dimensional from a usability standpoint due to the difficulties imposed by the need to navigate in three dimensions. The first paper of this thesis compares two user interfaces for the visualization of hierarchies, one two-dimensional and one three-dimensional. As we expected the three-dimensional tool excelled at tasks related to hierarchical depth while, surprisingly, the two tools perform comparably on most other tasks. A possible explanation for this is that we restrict manipulation in such a way that the user simply cannot get lost while navigating. Abrupt transitions cause confusion. This is a well known fact and in our second user study we set out to investigate what effect animated transitions would have on navigation in a 3D file system visualizer. The study we conducted failed to show an effect on user performance but did find an effect on navigation patterns. Participants were tasked to navigate stepwise into a directory and then, starting at the root, try to return to it (whichever way they chose). Participants in the animated treatment group were nearly four times as likely to take a shortcut back while participants in the non-animated group overwhelmingly favored a stepwise return strategy. The stepwise approach appears safer in that a percentage of shortcut attempts fail; failures which it seems difficult to recover from. The third and last paper is a survey and taxonomy of interactive animation in user interfaces. User interface animations are becoming more and more prevalent and advanced. Yet there is little in the way of research showing when you should animate and why. In the model underlying the taxonomy a number of aspects of animation are identified. Animation generally has a purpose, animation may catch attention, explain, smooth out abrupt transitions as well as reveal the progress of otherwise hidden processes. There is also a difference between transitional animations that preserve context and those that do not; a fact which is often overlooked. Of the user studies surveyed many show some benefit of animation but a significant number also show distinctly negative effects. Animation has been found to lead to superficial learning and poor retention when applied to teaching, as well as when it is used to smooth out abrupt transitions. / <p>Godkänd; 2006; 20070109 (haneit)</p>

In society today the production of energy has aimed its focus towards the resources that are renewable as a result of their ability to avoid negative effects of the environment. In the future it is desired to have replaced the current market entirely with these options which generates a demand to optimize these resources and their capabilities to produce energy. The current situation of production require separate systems to generate energy from a solar system and windmills which is a clear economic disadvantage.  Therefore it is highly desired to establish a solution to combine these two systems into one where they can generate energy collectively, this would result in the possibility to avoid unnecessary costs when these are desiderated to combine. Through development and executed testing’s a prototype has been created to counter this demand which will be presented in this thesis along with the positive effects this will have on the market of energy production concerning the environment as well as financially. The prototype has been created with the possibility to integrate a windmill into a solar system. Tests have been conducted in order to ensure that the project goals have been achieved. Through the execution of this project it has been determined that integration between a solar system and a windmill is feasible without major expenses. / I dagens samhälle har energiproduktionen riktat fokus mot de energikällor som är förnybara på grund av dess förmåga att undvika negativa effekter på miljön. I framtiden hoppas energiproduktionens nuvarande marknad vara helt ersatta med dessa alternativ vilket genererar ett behov av optimering av dessa energikällor och de möjligheter dessa innehar att producera energi. Den situation som vi befinner oss i idag kräver enskilda system för att möjliggöra utvinning av energi från vindkraftverk och solcellssystem. Då detta är ekonomiskt ofördelaktigt är det önskvärt att en lösning till detta problem etableras och på så sätt kan avsevärda kostnader undvikas i situationer där dessa system önskas kombineras vid elproduktion. I detta projekt har en prototyp framtagits som kombinerar ett solcellssystem med ett vindkraftverk. Det har gjorts tester för att se hur det befintliga solcellssystemet agerar vid anslutning av vindkraftverk och hur det går att anpassa vissa delar i systemet för att uppnå önskad funktionalitet. I slutet av projektet har det blivit klart att en integration mellan ett befintligt solcellssystem och ett vindkraftverk är möjligt. Systemet består av ett vindkraftverk som samverkar med ytterligare komponenter för att utvinna energi till en låg kostnad. Prototypen har mött de mål och krav som har ställts inom projektet med en möjlighet till vidareutveckling i framtiden.

This thesis presents a purposed navigation and control solution for autonomous ying of a quadrotor in conned spaces where positioning with GPS is notfeasible. The problem and related application considered is autonomous ying of a quadrotor in mineshafts for 3D modeling and inspection. Theoryand test results are presented including positioning experiments with a cameracombined with a UWB-ranging radio and a P-PI regulator for position control.It is argued that this is a viable and cost eective solution that can be usedto determine the position of the copter and control its position to within 0.2meters with stable controlled velocity.