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This paper addresses the need of continued education of process industry practitioners such as operators and instrumentation engineers. The process industry regulatory control tuning situation of today is reviewed. Areas of potential improvement are identified. A course, aimed at fulfilling these needs is presented. Especially, useful laboratory experiments are outlined. The suggested course was g
Two main topics are considered in this thesis: Machining with industrial robots and optimal control of road-vehicles in critical maneuvers. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of strong
This paper is based on a new procedure for dynamic output feedback design for systems with nonlinearities satisfying quadratic constraints. The new procedure is motivated by the challenges of output feedback control design for the 3-state Moore-Greitzer compressor model. First, we use conditions for stability of a transformed system and the associated matching conditions to find the data of the st
Feedback is an ancient idea, but feedback control is a young field. Nature long ago discovered feedback since it is essential for homeostasis and life. It was the key for harnessing power in the industrial revolution and is today found everywhere around us. Its development as a field involved contributions from engineers, mathematicians, economists and physicists. It is the first systems disciplin
This paper introduces a novel approach to building virtual laboratories of embedded control systems using TrueTime and Easy Java Simulations. TrueTime is a freeware MATLAB/Simulink based tool commonly used to simulate embedded control systems. Easy Java Simulations is a popular authoring tool that facilitates the creation of pedagogical simulations. According to the proposed approach, authors use
Abstract in UndeterminedStrong resilience properties of dynamical networks are analyzed for distributed routing policies. The latter are characterized by the property that the way the outflow at a non-destination node gets split among its outgoing links is allowed to depend only on local information about the current particle densities on the outgoing links. The strong resilience of the network is
One of the major research areas in computer vision is scene reconstruction from image streams. The advent of RGB-D cameras, such as the Microsoft Kinect, has lead to new possibilities for performing accurate and dense 3D reconstruction. There are already well-working algorithms to acquire 3D models from depth sensors, both for large and small scale scenes. However, these methods often break down w
New robotic applications often require physical interaction between the robot and its environment. To this purpose, external sensors might be needed, as well as a suitable way to specify the tasks. One complication that might cause problems in the task execution is orientation representation singularities. In this paper quaternions are used as a singularity-free orientation representation within t
This paper aims to address some gaps in current knowledge by studying temporal and spatial variations in Artemisia pollen counts (2000-2009) at 13 sites located in different biogeographical areas of Central and Eastern Europe. Analysis showed that start dates of Artemisia pollen seasons are greatly dependent on temperature during June and July, with hot summer temperatures having a tendency to del
Aquifers and groundwater-dependent ecosystems (GDEs) are facing increasing pressure from water consumption, irrigation and climate change. These pressures modify groundwater levels and their temporal patterns and threaten vital ecosystem services such as arable land irrigation and ecosystem water requirements, especially during droughts. This review examines climate change effects on groundwater a
This paper considers robust stability analysis of a large network of interconnected uncertain systems. To avoid analyzing the entire network as a single large, lumped system, we model the network interconnections with integral quadratic constraints. This approach yields a sparse linear matrix inequal- ity which can be decomposed into a set of smaller, coupled linear matrix inequalities. This allow
In this paper a controller reduction method for discrete-time linear time-invariant systems is described. Using the bounded-real lemma, the proposed method generates reduced controllers with closed loop stability and H-infinity norm performance guarantee. Information of the full controller is used as a basis for reduction using singular value decomposition. This is different from traditional model
In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix
Current market trends for industrial automation are the need for customizable production, shorter time to market, and powerful global competitive pressure. Based on these trends two challenges have been identified: 1) flexible production systems and 2) integration and utilization of devices and software. Applications from both process automation, manufacturing, and robotics have been considered.
An approach for merging statically schedulable subr egions in dataflow models is pr esented. The approach combines abstr act int erpr etation, loop analysis, and static scheduling of cyclo-static dataflow networ ks. The approach has been implemented in a Java-based tool that per forms automatic classification of dataflow act or s, generat ion of stat ic schedules using constr aint programming, and
This report addresses the related problems of trajectory generation and time-optimal path tracking with online obstacle avoidance. We consider the class of four-wheeled vehicles with independent steering and driving on each wheel, also referred to as pseudo-omnidirectional vehicles. Appropriate approximations of the dynamic model enable a convex reformulation of the path-tracking problem. Using th
We consider the problem of localizing a novel image in a large 3D model. In principle, this is just an instance of camera pose estimation, but the scale introduces some challenging problems. For one, it makes the correspondence problem very difficult and it is likely that there will be a significant rate of outliers to handle. In this paper we use recent theoretical as well as technical advances t
Embedded systems often operate in so variable con- ditions that design can only be carried out for some worst-case scenario. This leads to over-provisioned resources, and undue power consumption. Feedback control is an effective (and not yet fully explored) way to tailor resource usage online, thereby making the system behave and consume as if it was optimized for each specific utilization case. A
