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A methodology for estimating risks associated with landslides of contaminated soil into rivers.

Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in lands

Finding points of maximal loadability considering post-contingency corrective controls

Lately, much work in the area of voltage stability assessment has been focused on finding post-contingency corrective controls. In this article a contribution to this area will be presented where we search for maximal loadability while considering post-contingency corrective controls. This objective is different from the usual approach to the problem, where the aim is to include the post-contingen

Verifying Global Minima for L2 Minimization Problems in Multiple View Geometry

We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation, homography, camera resectioning and structure-and-motion with known rotatation, or known plane. Although optimal algorithms have been given for these problems under an Linfinity cost function, finding optimal least-squares solutions to these problems is difficult, since the cost functions are not

Efficient modeling of sun/shade canopy radiation dynamics explicitly accounting for scattering

Abstract in UndeterminedThe separation of global radiation (Rg) into its direct (Rb) and diffuse constituents (Rg) is important when modeling plant photosynthesis because a high Rd:Rg ratio has been shown to enhance Gross Primary Production (GPP). To include this effect in vegetation models, the plant canopy must be separated into sunlit and shaded leaves. However, because such models are often to

Toolbox for development and validation of grey-box building models for forecasting and control

As automatic sensing and information and communication technology get cheaper, building monitoring data becomes easier to obtain. The availability of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes the development and validation of a data-driven grey-box modelling toolbox for buildings. The Python toolbox is based on a Modelica library with th

General control-theoretical framework for online resource allocation in computing systems

System-theoretical methods are already used for the control of computing systems, but much more can be done exploiting said methods for their design. This requires to express in control-theoretical terms desires and specifications that originate in the computer science do- main, which may not be immediate. It also requires to accept that part of the addressed system be modified, which may pose som

The Optimal Sampling Pattern for Linear Control Systems

In digital control systems, the state is sampled at given sampling instants and the input is kept constant between two consecutive instants. With the optimal sampling problem, we mean the selection of sampling instants and control inputs, such that a given function of the state and input is minimized. In this paper, we formulate the optimal sampling problem and we derive a necessary condition of t

A Stochastic Optimal Power Flow Problem With Stability Constraints - Part II: The Optimization Problem

Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only limits on lineflows have been used as stability constraints. In many systems voltage stability and small-signal stability also play an important role i

Combination of Lyapunov and Density Functions for Stability of Rotational Motion

Lyapunov methods and density functions provide dual characterizations of the solutions of a nonlinear dynamic system. This work exploits the idea of combining both techniques, to yield stability results that are valid for almost all the solutions of the system. Based on the combination of Lyapunov and density functions, analysis methods are proposed for the derivation of almost input-to-state stab

A Stochastic Optimal Power Flow Problem With Stability Constraints - Part I: Approximating the Stability Boundary

Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only line flows have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constrai

Scalable stability conditions for heterogeneous networks via integral quadratic constraints

Decentralised and scalable conditions for robust stability of networks of heterogenous linear time-invariant (LTI) systems are derived based on integral quadratic constraints. These generalise previous works in the literature with an increased flexibility in the choice of multipliers employed. The results allow for arbitrary interconnection matrices and accommodate multi-input-multi-output systems

Initialization of the Kalman Filter without Assumptions on the Initial State

In absence of covariance data, Kalman filters are usually initialized by guessing the initial state. Making the variance of the initial state estimate large makes sure that the estimate converges quickly and that the influence of the initial guess soon will be negligible. If, however, only very few measurements are available during the estimation process and an estimate is wanted as soon as possib

Control and Design of Computing Systems: What to Model and How

The application of feedback control to computing systems is a promising research area, but has to date been hindered by the almost unanimously perceived complexity in creating control-oriented system models. Computing systems are in fact considered very hard to describe with dynamic models allowing for simple and powerful control design tools, so that complex ones need bringing in to the detriment

Increasing the Accuracy for a Piezo-Actuated Micro Manipulator for Industrial Robots using Model-Based Nonlinear Control

We consider the problem of modeling and control of the nonlinear dynamics of a micro manipulator, utilized for machining operations in combination with industrial robots. Position control of the micro manipulator is a challenging problem because of the actuation principle, which is based on piezo-actuators with inherent nonlinear behavior. The major nonlinearities in the manipulator are identified

Bayesian Combination of Multiple Plasma Glucose Predictors

This paper presents a novel on-line approach of merging multiple different predictors of plasma glucose into a single optimized prediction. Various different predictors are merged by recursive weighting into a single prediction using regularized optimization. The approach is evaluated on 12 data sets of type I diabetes data, using three parallel predictors. The performance of the combined predicti

Augmenting L1 Adaptive Control of Piecewise Constant Type to a Fighter Aircraft. Performance and Robustness Evaluation for Rapid Maneuvering

An L1 adaptive controller of piecewise constant type has been applied to a fighter aircraft by augmenting it to a linear state-feedback controller. Angle of attack and sideslip as well as velocity vector roll rate is demanded and controlled. It is relatively easy to design a controller augmentation this way; few parameters need to be tuned. To design an L1-controller for roll/pitch/yaw-motion of a

Towards a seamless integration between process modeling descriptions at Business and Production levels - work in progress

To fulfill increasing requirements in the manufacturing sector, companies are faced with several challenges. Three major challenges have been identified regarding time-to-market, vertical feedback loops and level of automation. Grafchart, a graphical language aimed for supervisory control applications, can be used from the process-planning phase, through the implementation phase and all the way to

Stability and Worst-Case Performance Analysis of Sampled-Data Control Systems with Input and Output Jitter

When a feedback controller is implemented in a networked embedded system, the computations and communications induce delays and jitter, which may destabilize the control loop. The majority of previous work on analysis of control loops with time-varying delays has focused on output (actuation) jitter. In many embedded systems, input (sampling) jitter is also an issue. In this paper, we analyze the