<p>A modern fighter aircraft is exposed to very different flight conditions and must despite that perform infallibly in every single situation. Several variables like center of gravity, speed, altitude and weight vary during a standard mission flight or</p><p>between flights. For the aircraft to be able to perform effectively, superior manoeuvrability is vital. Hence it is of great importance that the flight control system is capable to cope with these different variations.</p><p>In the 1960s professor Isaac Horowitz presented the method Quantitative feedback theory (QFT) which is a method whose aim is to manage system variations. The method can be useful in the construction of the control system for a fighter aircraft. QFT is a frequency based method whose main objective is to shape the</p><p>open loop gain in a Nicholschart to meet the required closed loop demands. A prefilter is then applied to achieve correct reference tracking.</p><p>This thesis is divided into two parts, where the first part presents the method QFT for both the SISO-systems and for the MIMO-systems. For the MIMOsystems several design techniques are presented, the chapter also includes a method on the implementation of state feedback. Furthermore statements of how nonlinear and unstable systems are handled with the QFT is included.</p><p>The second part of the thesis presents the design of a control system for an unstable fighter aircraft. The design is constructed for the SISO longitudinal dynamics as well as for the MIMO lateral dynamics, where the design must be robust against variations in speed, altitude and center of gravity.</p><p>The flight control system that is implemented meets almost all requirements and gives good preformance and this is achieved with only a few regulators. Proposals of possible solutions to those requirements note yet reached are discusssed.</p>

<p>The purpose of this thesis is to examine and present the oportunities of solving</p><p>control problems using Modelica. This is done by creating some demonstration</p><p>examples with exercises. These examples should cover as many types of control</p><p>problems as possible. The exercises are aimed for people with basic knowledge</p><p>in modeling and automatic control engineering but with little or no knowledge</p><p>in Modelica. There are different types of Modelica implementations and the ones</p><p>used in this thesis are OpenModelica and MathModelica.</p>

<p>At working sites all around monotonic tasks are performed. If one were able</p><p>to automatize these kinds of tasks there would be a large economical profit to</p><p>collect. Volvo CE are in the process of developing an autonomous wheel loader,</p><p>to perform these types of monotonic, uniform tasks. The project is intended to</p><p>be performed mainly be thesis workers. This report is the eighth thesis in this</p><p>project. Earlier work has made the loader able to see a pile using a laser scanner.</p><p>The machine can also see and fill a hauler. The usage of the laser scanner can</p><p>only be made while the loader is standing still. The aim of this thesis work has</p><p>been to make the loader able to scan its environment while it is moving. To do</p><p>this an inertial measurement unit has been used for keeping track of the scanners</p><p>orientation during a scan. The work of this thesis has resulted in a working set-up</p><p>on the machine, and a robust framework for future work.</p><p> </p>

<p>Detta examensarbete är en del av SNOD-projektet vid Totalförsvarets Forskningsinstitut (FOI), vars syfte är att utveckla ett sensorsystem med infraröda- och videosensorer och integrerat navigationssystem. Sensorsystemet är placerat i en kameragimbal och kan användas på rörliga plattformar, t ex UAV:er, för övervakning och rekognoscering. Gimbalen är till för att möjliggöra inriktning av sensorerna i önskad riktning.</p><p>Detta examensarbete behandlar en metod för inmätning av målkoordinater från den rörliga plattformen, det s k QWIP/MASP-systemet. Detta efterliknar ett UAV-system. Metoden för inmätning baseras på ett extended information filter där målkoordinaterna filtreras fram. Mätningarna bygger på data från en bildbaserad målföljare med på IR- och videodata.</p><p>För att förbättra inmätningen har en metod för planering av plattformens rörelsebana tagits fram. Denna metod bygger en referensbana för plattformen som maximerar informationen i informationsfiltret.</p><p>Metoderna har utvecklats för implementering i den aktuella sensorplattformen, QWIP/MASP-systemet. För att övervaka och styra denna plattform har ett grafiskt användargränssnitt tagits fram för operatörsstöd.</p> / <p>This thesis is a part of the SNOD project at Swedish Defence Research Agency (FOI), which aims at developing a sensor system consisting of infrared and video sensors and an integrated navigation system. The sensor system is placed in a camera gimbal and will be used on moving platforms, e.g. UAVs, for surveillance and reconnaissance. The gimbal is a device that makes it possible for sensors to be pointed in a desired direction.</p><p>In this thesis a method for estimating target position using a moving platform is discussed. This method is based on the extended information filter, where bearingonly measurements are given by infrared and video images processed through a target tracker. Tests and evaluations are done with data from the QWIP/MASP-system, which is an UAV surrogate developed at FOI.</p><p>To improve target position estimation, a path planning method using information theory has been developed. This method is based on maximizing the expected information of the information filter.</p><p>These methods have been developed for implementation in the QWIP/MASP-system. A user interface for this system has also been developed to support the operator.</p>

<p>The power to mass ratio of a heavy truck causes even moderate slopes to have a significant influence on the motion. The velocity will inevitable vary within an interval that is primarily determined by the ratio and the road topography. If further variations are actuated by a controller, there is a potential to lower the fuel consumption by taking the upcoming topography into account. This possibility is explored through theoretical and simulation studies as well as experiments in this work.</p><p>Look-ahead control is a predictive strategy that repeatedly solves an optimization problem online by means of a tailored dynamic programming algorithm. The scenario in this work is a drive mission for a heavy diesel truck where the route is known. It is assumed that there is road data on-board and that the current heading is known. A look-ahead controller is then developed to minimize fuel consumption and trip time.</p><p>The look-ahead control is realized and evaluated in a demonstrator vehicle and further studied in simulations. In the prototype demonstration, information about the road slope ahead is extracted from an on-board database in combination with a GPS unit. The algorithm calculates the optimal velocity trajectory online and feeds the conventional cruise controller with new set points. The results from the experiments and simulations confirm that look-ahead control reduces the fuel consumption without increasing the travel time. Also, the number of gear shifts is reduced. Drivers and passengers that have participated in tests and demonstrations have perceived the vehicle behavior as comfortable and natural.</p> / Report code: LIU-TEK-LIC-2007:28.

Piloting a commercial aircraft involves performing multiple tasks in a real-time environment that require pilot's attention and cognitive resource allocation. Due to resource limitation, pilots must perform cockpit task management (CTM) because they cannot perform all tasks that demand their attention at once. Hence, pilots must prioritize the tasks in the order of most to least important and allocate their resources according to this prioritization. Over the years, pilots have developed rules of thumb for task prioritization in facilitating CTM. A task prioritization error is simply an error made by the flight crew when they perform lower priority tasks as opposed to higher priority tasks, where priority is determined by the Aviate-Navigate-Communicate-Manage Systems (A-N-C-S) task ordering. Although the level of flight deck automation has been suggested as one factor influencing the likelihood of task prioritization errors, there has so far been just one study directed towards confirming that hypothesis. Hence the first objective of this study was to determine the effect of the level of automation on CTM performance. CTM performance was measured by looking at the number of task prioritization errors committed by pilots in different levels of automation. In addition to the level of automation, there was also reason to believe that the pilot's automation proficiency might affect CTM performance. Therefore, the second objective of this study was to determine the effect of automation proficiency on CTM performance. Nine airline transport pilots served as subjects in this study. Three flying scenarios and three levels of flight deck automation were simulated on a part-task flight simulator. Each pilot ran three different combinations of flight deck automation and flying scenario. The CTM performance for each pilot was determined by identifying the number of task prioritization errors committed in each experiment run. The average number of errors in different levels of automation and automation proficiency were compared for their effect on CTM performance using Analysis of Variance (ANOVA). It was found that the level of automation affected CTM performance depending scenarios in which phases of flight differed. However, automation proficiency, measured by glass cockpit hours, was found to have no effect on CTM performance. / Graduation date: 2000

In real-time control systems, the value of a control decision depends not only on the correctness of the decision but also on the time when that decision is available. Recent work in real-time decision making has used machine learning techniques to automatically construct reactive controllers, that is, controllers with little or no internal state and low time complexity pathways between sensors and effectors. This paper presents research on 1) how a problem representation affects the trade-offs between space and performance, and 2) off -line versus on-line approaches for collecting training examples when using machine learning techniques to construct reactive controllers. Empirical results show that for a partially observable problem both the inclusion of history information in the problem representation and the use of on-line rather than off -line learning can improve the performance of the reactive controller. / Graduation date: 1994

Scania är en välkänd tillverkare av tunga lastfordon och bussar. De profilerar sig som det presigefyllda valet med hög teknologinivå. För att kunna leda utvecklingen av nya funktioner och motorer måste många tester av alla system i dessa fordon göras. Till detta används provceller speciellt ordnade för specifika lastbilskomponenter och många av dessa komponenter behöver en yttre kylning under drift varför flera av provcellerna har reglerade kylsystem. Vid uppgradering av kylsystem eller nybyggnation av provceller med kylsystem finns en önskan att kunna simulera och göra tester av kylsystemet innan det faktiska kylsystemet finns på plats, för att säkerställa prestandan innan någon investering görs. Detta examensarbete går ut på att genom att skapa vissa basmodeller för komponenter i kylsystem, möjliggöra simulering av godtyckliga kylsystem för utvärdering av olika reglerstrategier, designer och deras prestanda. Vid framtagning av modellerna användes mestadels fysikalisk modellering men även rent praktiska modeller för att fylla en funktion existerar. Det resulterande modellbiblioteket klarar av att visa dynamiska effekter mycket bra men dess statiska träffsäkerhet är inte lika exakt. Dynamiken är dock det viktiga och svårt att få fram på andra sätt, varför modellbiblioteket kan vara användbart vid bedömningar om reglerstrategier och prestanda. / Scania is a wellknown manufacturer of heavy transport vehicles such as trucks and buses. Their profile is to be the prestigeous choice with a high level of technology. To maintain the leading position in development of new functionality and engines, substantial testing is nessecary. This is accomplished by using testbeds specialized for different components and purposes. Many of these components need external cooling during operation which is why a cooling system is present in a large number of testbeds. When new testbeds are to be constructed or an old cooling system is to be redesigned, there is a desire to be able to simulate and run tests of the cooling system before the actual cooling system is in place, to make sure performance is at a high enough level, before any investment is made. The task in this master thesis is to construct, in a matlab and simulink environment, a set of base models for cooling system components. With this set, arbitrary cooling systems can be constructed and simulated to evaluate different designes, control strategies and performance. Physical modelling was the most common method when constucting the base models though some models have a pure practical function. The resulting model library is able to, when put together to a complete cooling system, show dynamic behaviour correctly but static accuracy is a bit off. When judging a new control strategy, dynamic behaviour is the most important aspect, and also the most difficult to get elsewhere, which is why the model library can still be very useful.

A model is developed for the Quanser torsion system available at Control Systems Research Laboratory at Chulalongkorn University. The torsion system is a laboratory equipment that is designed for the study of position control. It consists of a DC motor that drives three inertial loads that are coupled in series with the motor, and where all components are coupled to each other through torsional springs. Several nonlinearities are observed and the most significant one is an offset in the input signal, which is compensated for. Experiments are carried out under feedback as the system is marginally stable. Different input signals are tested and used for system identification. Linear black-box state-space models are then identified using PEM, N4SID and a subspace method made for closed-loop identification, where the last two are the most successful ones. PEM is used in a second step and successfully enhances the parameter estimates from the other algorithms.

AIMS AB is a Swedish company that develops and sells inertial sensor systems. A new product is under research which basically is an aided inertial navigation system where unwanted drift is eliminated. This can be done by integrating a GPS reciever into the system and fuse measurement data from GPS and IMU. Such a product is useful in racing, where engineers always are searching for the optimal performance and the shortest lap times. Today the only feedback the engineers and mechanics get from their work is the driver’s comments and lap times. It would be of great help if it was possible to see the behaviour of the car directly in technical terms. The focus of this master thesis is fusing a GPS receiver and an IMU using an Extended Kalman Filter (EKF). The main task of the EKF is to estimate the errors of the intertial measurements and correct the measurements to eliminate drift in velocity and position. To verify the system, data collection was done togheter with the team G2 Racing and Tony Ring. The measurements were done in Tony’s Ferrari F430 Pista during two days at the Paul Ricard circuit in southern France. From the results possibilites to further estimate interesting entities were evaluated. / AIMS AB är ett företag som tillverkar och säljer olika typer av tröghetsnavigeringssystem. En ny produkt med ett tröghetsnavigeringssystem stöttat av GPS är under utveckling. Med sensorfusion kan GPS- och IMU-mätningar integreras genom användning av ett Extended Kalman Filter (EKF). Ett sådant system kan komma till användning inom racing där strävan efter optimal prestanda och korta varvtider är stor. Den information ingenjörerna får om bilens beteende är ofta enbart förarens kommentarer. Förarens beskrivning kan ofta vara svår att översätta till tekniska termer som behövs för att enkelt justera inställningar och nå önskade egenskaper. Det skulle vara till stor hjälp om ingenjörerna direkt fick tillgång till teknisk information om fordonets beteende. I detta examensarbete ligger fokus på sensorfusion av GPS- och IMU-mätningar genom användning av ett Extended Kalman Filter (EKF). Huvuduppgiften för kalmanfiltret är att skatta fel i mätningar av accelerationer och vinkelhastigheter så att korrigering för dessa kan göras och därmed drift i position elimineras. För verifiering av systemet har datainsamling utförts tillsammans med teamet G2 Racing och Tony Ring. Mätningnarna är gjorda i Tonys Ferrari F430 Pista under två dagar på banan Paul Ricard i södra Frankrike. Ur resultatet undersöks även möjligheterna till vidare skattning av intressanta data som kan vara till hjälp för ingenjörerna i ett racingteam.