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Designing High-Quality Embedded Control Systems with Guaranteed Stability

Many embedded systems comprise several controllers sharing available resources. It is well known that such resource sharing leads to complex timing behavior that degrades the quality of control, and more importantly, can jeopardize stability in the worst-case, if not properly taken into account during design. Although stability of the control applications is absolutely essential, a design flow dri

Autotuning control structures for reliability-driven dynamic binding

This paper explores a formally grounded ap- proach to solve the problem of dynamic binding in service- oriented software architecture. Dynamic binding is a widely adopted mean to automatically bind exposed software interfaces to actual implementations. The execution of an operation on one or another implementation, though providing the same result, could turn out in different quality of service, e

Modeling regional sediment transport and shoreline response in the vicinity of tidal inlets on the Long Island coast, United States

A new numerical model was developed to simulate regional sediment transport and shoreline response in the vicinity of tidal inlets based on the one-line theory combined with the reservoir analogy approach for volumetric evolution of inlet shoals. Sand bypassing onshore and sheltering effects on wave action from the inlet bar and shoals were taken into account. The model was applied to unique field

Plant and Vegetation Dynamics on Disko Island, West Greenland: Snapshots Separated by Over 40 Years

We report on a revisit in 2009 to sites where vegetation was recorded in 1967 and 1970 on Disko Island, West Greenland. Re-sampling of the same clones of the grass Phleum alpinum after 39 years showed complete stability in biometrics but dramatic earlier onset of various phenological stages that were not related to changes in population density. In a fell-field community, there was a net species l

Developing a module for estimating climate warming effects on hydropower pricing in California

Climate warming is expected to alter hydropower generation in California through affecting the annual stream-flow regimes and reducing snowpack. On the other hand, increased temperatures are expected to increase hydropower demand for cooling in warm periods while decreasing demand for heating in winter, subsequently altering the annual hydropower pricing patterns. The resulting variations in hydro

Efficient Structure and Motion: Path Planning, Uncertainty and Sparsity

This thesis explores methods for solving the structure-and-motion problem in computer vision, the recovery of three-dimensional data from a series of two-dimensional image projections. The first paper investigates an alternative state space parametrization for use with the Kalman filter approach to simultaneous localization and mapping, and shows it has superior convergence properties compared wit

Outlier Removal Using Duality

In this paper we consider the problem of outlier removal for large scale multiview reconstruction problems. An efficient and very popular method for this task is RANSAC. However, as RANSAC only works on a subset of the images, mismatches in longer point tracks may go ndetected. To deal with this problem we would like to have, as a post processing step to RANSAC, a method that works on the entire (

Volatility of Organic Aerosol: Evaporation of Ammonium Sulfate/Succinic Acid Aqueous Solution Droplets

Condensation and evaporation modify the properties and effects of atmospheric aerosol particles. We studied the evaporation of aqueous succinic acid and succinic acid/ammonium sulfate droplets to obtain insights on the effect of ammonium sulfate on the gas/particle partitioning of atmospheric organic acids. Droplet evaporation in a laminar flow tube was measured in a Tandem Differential Mobility A

Output feedback distributed model predictive control with inherent robustness properties

We consider robust output feedback distributed model predictive control (DMPC). The proposed controller is based on the results in [8] in which nominal stability and feasibility was proven for a DMPC-formulation without terminal constraint set or terminal cost in the optimization. We extend these results to show robust stability under state feedback as well as output feedback when dynamics and mea

From Competitive to Cooperative Resource Management for Cyber-Physical Systems

This thesis presents models and methods for feedback-based resource management for cyber-physical systems. Common for the scenarios considered are severe resource constraints, uncertain and time-varying conditions and the goal of enabling flexibility in systems design rather than restricting it. A brief survey on reservation-based scheduling, an important enabling technology for this thesis, is pr

Learning Approach to Cycle-Time-Minimization of Wood Milling Using Adaptive Force Control

A majority of the machining processes in the industry of today is performed using position-controlled machine tools, where conservative feed rates have to be used in order to avoid excessive process forces. By instead controlling the process forces, the feed rate, and consequently the material removal rate, can be maximized. In turn, this leads to decreased cycle times and cost savings. Furthermor

Joint Pose and Radio Channel Estimation

This thesis investigates the combination of pose and radio channel estimation. Pose is the knowledge of the position and orientation of a device whereas the radio channel describes the transmission medium between radio transmitters and receivers. The two subjects are both active research topics with a long history of applications but there has to the author's knowledge been very little work publis

Revisiting Trifocal Tensor Estimation Using Lines

In this paper, we revisit the problem of estimating the trifocal tensor from image line measurements. With measurements of corresponding lines in three views, a linear method [1] requiring 13 lines was developed to estimate the trifocal tensor from which projective reconstruction of the scene is made possible. By further utilizing the nonlinear constraints on the trifocal tensor, we propose severa

A generalized distributed accelerated gradient method for distributed model predictive control with iteration complexity bounds

Most distributed optimization methods used for distributed model predictive control (DMPC) are gradient based. Gradient based optimization algorithms are known to have iterations of low complexity. However, the number of iterations needed to achieve satisfactory accuracy might be significant. This is not a desirable characteristic for distributed optimization in distributed model predictive contro

Multi-scale structured imaging using wave packets and prolate spheroidal wave functions

Imaging and inverse scattering of seismic reflection data can be formulated in terms of a certain class of Fourier integral operators. We present an approximation and discretization of such operators following a multiscale approach, based on wave packets as the quanta for representing seismic data. One of the key ingredients in our approach is the coupling of dyadic parabolic decomposition and pro

Distributed Management of CPU Resources for Time-Sensitive Applications

The number of applications sharing the same embedded device is increasing dramatically. Very efficient mechanisms (resource managers) for assigning the CPU time to all demanding aplications are needed. Unfortunately existing optimization-based resource managers consume too much resource themselves. In this paper, we address the problem of distributed convergence to efficient CPU allocation for ti