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A Singular Value Decomposition Based Closed Loop Stability Preserving Controller Reduction Method

In this paper a controller reduction method which preserves closed loop stability is described. A Lyapunov inequality based sufficient condition is proposed in the search of the reduced controller. The reduced controller leads to a stable closed loop system with guaranteed approximation quality. Furthermore, the proposed problem can be formulated as a matrix approximation problem which can be solv

Wave Damping in Reed: Field Measurements and Mathematical Modeling

Wave damping in vegetation in shallow lakes reduces resuspension and thereby improves the light climate and decreases nutrient recycling. In this study, wave transformation in reed (Phragmites australis) was measured in a shallow lake. Theoretical models of wave height decay, based on linear wave theory, and transformation of the probability density function (PDF), using a wave-by-wave approach, w

Fast and Reliable Two-View Translation Estimation

It has long been recognized that one of the fundamental difficulties in the estimation of two-view epipolar geometry is the capability of handling outliers. In this paper, we develop a fast and tractable algorithm that maximizes the number of inliers under the assumption of a purely translating camera. Compared to classical random sampling methods, our approach is guaranteed to compute the optimal

Analysis of Linear L1 Adaptive Control Architectures for Aerospace Applications

In some situations the closed-loop system obtained by L1 adaptive control is equivalent to linear systems. The architectures of these systems are investigated and compared with internal model control and the input observer architecture. The analysis is focused on aerospace application. An effort has been made to understand and describe what fundamental control characteristic of flying applications

Forecasting monthly precipitation in Central Chile: a self-organizing map approach using filtered sea surface temperature

Western South America is subject to considerable inter-annual variability due to El Nio-Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperat

Climate change impacts on high-elevation hydroelectricity in California

While only about 30% of California's usable water storage capacity lies at higher elevations, high-elevation (above 300 m) hydropower units generate, on average, 74% of California's in-state hydroelectricity. In general, high-elevation plants have small man-made reservoirs and rely mainly on snowpack. Their low built-in storage capacity is a concern with regard to climate warming. Snowmelt is expe

Robust Stability Analysis of Sparsely Interconnected Uncertain Systems

In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertain systems. By modeling the interconnections among the subsystems with integral quadratic constraints, we show that robust stability analysis of such systems can be performed by solving a set of sparse linear matrix inequalities. We also show that a sparse formulation of the analysis problem is equiv

Joint Positioning and Multipath Radio Channel Estimation and Prediction

This thesis investigates the topic of joint positioning and radio channel estimation and prediction. Both positioning and radio channel estimation have a long history of research with many publications but the combination of the two has so far at large been left unexplored. The reason for studying this topic is twofold: improvement of positioning and improvement of radio channel prediction. Positi

FLOPSYNC-2: efficient monotonic clock synchronisation

Time synchronisation is crucial for distributed systems, and particularly for Wireless Sensor Networks (WSNs), where each node is executing concurrent operations to achieve a real-time objective. However, synchronisation is quite difficult to achieve in WSNs, due to the unpredictable deployment conditions and to physical effects like thermal stress, that cause drifts in the local node clocks. As a

Accelerated gradient methods and dual decomposition in distributed model predictive control

We propose a distributed optimization algorithm for mixed L_1/L_2-norm optimization based on accelerated gradient methods using dual decomposition. The algorithm achieves convergence rate O(1/k^2), where k is the iteration number, which significantly improves the convergence rates of existing duality-based distributed optimization algorithms that achieve O(1/k). The performance of the developed al

Autonomous Framework for Segmenting Robot Trajectories of Manipulation Task

In manipulation tasks, motion trajectories are characterized by a set of key phases (i.e., motion primitives). It is therefore important to learn the motion primitives embedded in such tasks from a complete demonstration. In this paper, we propose a core framework that autonomously segments motion trajectories to support the learning of motion primitives. For this purpose, a set of segmentation po

Simulated Mid-ranging Control of Propofol and Remifentanil using EEG-measured Hypnotic Depth of Anesthesia

This paper suggests an extension of an existing, clinically evaluated, closed-loop drug delivery system for hypnotic depth control using propofol. The extension introduces closed-loop administration of the analgesic drug remifentanil, thus forming a multiple input–single output (MISO) control system. Remifentanil acts and is metabolized at a significantly faster time scale than propofol. Direct co

A Game-Theoretic Resource Manager for RT Applications

The management of resources among competing QoS-aware applications is often solved by a resource manager (RM) that assigns both the resources and the application service levels. However, this approach requires all applications to inform the RM of the available service levels. Then, the RM has to maximize the "overall quality" by comparing service levels of different applications which are not nece

Topics in Machining with Industrial Robot Manipulators and Optimal Motion Control

Two main topics are considered in this thesis: Machining with industrial robot manipulators and optimal motion control of robots and vehicles. 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 the

Robotic Work-Space Sensing and Control

Industrial robots are traditionally programmed using only the internal joint position sensors, in a sense leaving the robot blind and numb. Using external sensors, such as cameras and force sensors, allows the robot to detect the existence and position of objects in an unstructured environment, and to handle contact situations not possible using only position control. This thesis presents work on

On Robotic Assembly using Contact Force Control and Estimation

Force sensing provides robots the capability to accomplish tasks where physical interaction with the environment is required, such as assembly. Small position uncertainties can then be corrected for by sensing the contact forces. This thesis considers the problem of force-controlled assembly, including how tasks can be specified in a simple and intuitive way and how robust task execution under unc

WRF-SBM Simulations of Melting-Layer Structure in Mixed-Phase Precipitation Events Observed during LPVEx

Two mixed-phase precipitation events were observed on 21 September and 20 October 2010 over the southern part of Finland during the Light Precipitation Validation Experiment (LPVEx). These events have been simulated using the Weather Research and Forecasting Model coupled with spectral bin microphysics (WRF-SBM). The detailed ice-melting scheme with prognosis of the liquid water fraction during me

Introducing Service-level Awareness in the Cloud

Resource allocation in clouds is mostly done assuming hard requirements, applications either receive the requested resources or fail. Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient. To solve this issue, we introduce Service Level (SL) awareness in clouds, assuming applicati