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The Integral Quadratic Constraint (IQC) framework developed by Professor Yakubovich and his co-workers, see Yakubovich et.al. (2004), is one of few available constructive tools for establishing robust stability of nonlinear systems. An explicit format of stability conditions, procedures for computing a Lyapunov function and developed libraries IQCs for common nonlinearities in dynamics, all togeth
An extended Kalman-Yakubovich-Popov Lemma for positive systems is proved, which generalizes earlier versions in several respects: Non-strict inequalities are treated. Matrix assumptions are less restrictive. Moreover, a new equivalence is introduced in terms of linear programming rather than semi-definite programming. As a complement, we also prove that a symmetric Metzler matrix with rn non-zero
Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They need to make better use of plant data, ideally utilising all data from the entire plant. Low-level data should be refined toreal-time information for decision-making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architecture (LIS
This paper is about line search for the generalized alternating projections (GAP) method. This method is a generalization of the von Neumann alternating projections method, where instead of performing alternating projections, relaxed projections are alternated. The method can be interpreted as an averaged iteration of a nonexpansive mapping. Therefore, a recently proposed line search method for su
This paper presents a simple and effective way of solving the robust subspace estimation problem where the corruptions are column-wise. The method we present can handle a large class of robust loss functions and is simple to implement. It is based on Iteratively Reweighted Least Squares (IRLS) and works in an iterative manner by solving a weighted least-squares rank-constrained problem in every it
A general framework for analysing robust synchronization in large-scale heterogenous networks is proposed based on the theory of integral quadratic constraints (IQCs). Dynamic agents are represented as linear time-invariant single-input-single-output systems. The agents exchange information according to a sparse dynamical interconnection operator in order to achieve synchronization, where their ou
A novel automatic tuning strategy is proposed. It is based on an experiment of very short duration, followed by simultaneous identification of LTI model parameters and an estimate of their error covariance. The parametric uncertainty model is subsequently exploited to design linear controllers with magnitude bounds on some closed-loop transfer function of interest, such as the sensitivity function
A novel autotuning procedure is presented through application to an industrial in-line pH control system. The procedure has three advantages over classical relay auto-tuners: experiment duration is very short (no need for limit-cycle convergence); all data is used for identification (instead of only peaks and switch instances); a parameter uncertainty model is identified and utilized for robust co
For many assembly operations force control is needed, but force sensors may be expensive and add mass to the system. An alternative is to use the motor torques, though friction causes large disturbances. The Coulomb friction can be quite well known when a joint is moving, but has much larger uncertainties for velocities close to zero. This paper presents a method for force estimation that account
We have developed the novel Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas-phase Master Chemical Mechanism version 3.2 (MCMv3.2), an aerosol dynamics and particle-phase chemistry module (which considers acid-catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interac
One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this pa
We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approximate solutions of hard problems. An extensive set of experiments are performed for a variety of application problems including graph cut segmentation, curvature regularization and more
We consider the problem of distributed convergence to efficient outcomes in coordination games through dynamics based on aspiration learning. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process in terms of an equivalent finite-state Markov chain. We then characterize explicitly the behavior of the proposed aspiration learnin
A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km x 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m x 400 m for selected areas in De
Cluster analysis of particle number size distributions from background sites across Europe is presented. This generated a total of nine clusters of particle size distributions which could be further combined into two main groups, namely: a south-to-north category (four clusters) and a west-to-east category (five clusters). The first group was identified as most frequently being detected inside and
We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schemes. The formulation is based on a cell complex and considers basic regions and bou
We construct a variational formulation for the problem of interpolating seismic data in the case of missing traces. We assume that we have derivative information available at the traces. The variational problem is essentially the minimization of the integral over the smallest eigenvalue of the structure tensor associated with the interpolated data. This has the physical meaning of penalizing the l
This paper focuses on the computation of the joint spectral radius (JSR), when the involved matrices are sparse. We provide a sparse variant of the procedure proposed by Parrilo and Jadbabaie to compute upper bounds of the JSR by means of sum-of-squares (SOS) programming. Our resulting iterative algorithm, called SparseJSR, is based on the term sparsity SOS (TSSOS) framework developed by Wang, Mag
Industrial control systems (ICSs) are a significant part of industry and they play an important role in monitoring and controlling industrial processes. Traditionally, ICSs have been isolated from the Internet, and thereby secured from various Internet-based security threats. In recent years, since the cloud can provide huge advantages regarding storage and computing resources, industry has been m
Camera sensor networks, mainly with surveillance cameras, are growing in size and complexity. Storage space is the prime resource in such systems but current surveillance setups are still very much centralized and limited in resources due to cost and security constraints. Allocating the correct amount of storage to each camera sensor considering their large difference in characteristics and video
