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A Result for Orthogonal Plus Rank-1 Matrices

In this paper the sum of an orthogonal matrix and an outer product is studied, and a relation between the norms of the vectors forming the outer product and the singular values of the resulting matrix is presented. The main result may be found in Theorem 1.

Operator splitting performance estimation : Tight contraction factors and optimal parameter selection

We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the methodology as a tool for computerassisted proofs to prove tight analytical contraction factors for Douglas-Rachford splitting that are likely too complicated for a

MSE-optimal measurement dimension reduction in gaussian filtering

We present a framework for measurement dimension reduction in Gaussian filtering, defined in terms of a linear operator acting on the measurement vector. This operator is optimized to minimize the Cramér-Rao bound of the estimate's mean squared error (MSE), yielding a measurement subspace from which elements minimally worsen the filter MSE performance, as compared to filtering with the original me

INTERNET OF THINGS AS A COMPLEMENT TO INCREASE SAFETY

Safety evaluations made in the city Helsingborg indicate a decreased risk of being exposed to crime, but an increased feeling of unsafe. Damage in the form of scribbling (graffiti) is one of several indicators contributing to feeling unsafe. In this paper we investigate whether the use of Internet­-of-­things technology, where a sensor monitors a walking and cycling tunnel, makes it possible to re

On LQG-Optimal Event-Based Sampling

Event-based control is a promising concept for the design of resource-efficient feedback systems, where events such as sampling, actuation, and data transmissions are triggered reactively based on monitored control performance rather than a periodic timer. In this thesis, we investigate how sampling and communication events should be triggered to fully exploit the potential of event-based control

Neural-Network-Based Adaptive Control for Bilateral Teleoperation with Multiple Slaves under Round-Robin Scheduling Protocol

A neural-network-based adaptive control scheme is developed for bilateral teleoperation systems with single-master-multiple-slaves in the presence of dynamic uncertainties and communication constraint. Discrete-time data transmitting communication network with bandwidth limitation and time-varying communication delays is considered and the Round-Robin scheduling protocol is used to orchestrate the

Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes

Ship traffic is a major source of aerosol particles, particularly near shipping lanes and harbours. In order to estimate the contribution to exposure downwind of a shipping lane, it is important to be able to measure the ship emission contribution at various distances from the source. We report on measurements of atmospheric particles 7-20 km downwind of a shipping lane in the Baltic Se

Realizability and internal model control on networks

It is proved that network realizability of controllers can be enforced without conservatism using convex constraints on the closed loop transfer function. Once a network realizable closed loop transfer matrix has been found, a corresponding controller can be implemented using a network structured version of Internal Model Control.

Optimality interpretations for atomic norms

Atomic norms occur frequently in data science and engineering problems such as matrix completion, sparse linear regression, system identification and many more. These norms are often used to convexify non-convex optimization problems, which are convex apart from the solution lying in a non-convex set of so-called atoms. For the convex part being a linear constraint, the ability of several atomic n

Sparsity-constrained optimization of inputs to second-order systems

We propose an efficient algorithm, that given a strictly proper, second-order system, finds a sparse input signal so that the system's output optimally approximates a given trajectory in least-squares sense. As an illustration, we apply the algorithm to an estimation problem from medicine.

Using Radial Basis Functions to Approximate the LQG-Optimal Event-Based Sampling Policy

A numerical method based on radial basis functions (RBF) has been developed to find the optimal event-based sampling policy in an LQG problem setting. The optimal sampling problem can be posed as a stationary partial differential equation with a free boundary, which is solved by reformulatingthe optimal RBF approximation as a linear complementarity problem (LCP). The LCP can be efficiently solved

Towards real-time ADMM for linear MPC

We present a novel predictive control scheme for linear constrained systems that uses the alternating direction method of multipliers (ADMM) for online optimization. In contrast to existing works on ADMM-based model predictive control (MPC), we only consider a single ADMM-iteration in every time step. The resulting real-time ADMM scheme is tailored for embedded and fast MPC implementations. The ma

Novel insights on new particle formation derived from a pan-european observing system

The formation of new atmospheric particles involves an initial step forming stable clusters less than a nanometre in size (<~1 nm), followed by growth into quasi-stable aerosol particles a few nanometres (~1-10 nm) and larger (>~10 nm). Although at times, the same species can be responsible for both processes, it is thought that more generally each step comprises differing chemical contributors. H

Polynomial Reconstruction of 3D sampled Curves Using Auxiliary Surface Data

This paper proposes a method for structural enhancement of a 3D sampled curve. The curve is assumed to be organized, but corrupted with low frequency noise. The proposed method approaches the notion of curve reconstruction in a novel way, where information about the structure in a scanned surface is used to reconstruct the curve. Principal Component Analysis is carried out on successive neighborho

IEEE Std. P1687.1 for Access Control of Reconfigurable Scan Networks

We address access control of reconfigurable scan networks, like IEEE Std. 1687 networks. We propose an on- chip test block to perform: (1) test for faulty scan-chains, (2) localization of faulty scan-chains and (3) repair by excluding faulty scan-chains, and an access control block to (1) control so scan- chains (instruments) are only accessed in allowed combinations, (2) detection of access attem

Closed-form H-infinity optimal control for a class of infinite-dimensional systems

H-infinity optimal control and estimation are addressed for a class of systems governed by partial differential equations with bounded input and output operators. Diffusion equations are an important example in this class. Explicit formulas for the optimal state feedback controller as well as the optimal state estimator are given. Unlike traditional methods for H-infinity synthesis, no iteration i

A high precision logarithmic-curvature compensated all CMOS voltage reference

This paper presents a resistor-less high-precision, sub-1 V all-CMOS voltage reference. A curvature-compensation method is used to cancel the logarithmic temperature dependence regardless of mobility temperature exponent (γ). The circuit is simulated in 65 nm CMOS technology and yields an output voltage of 594 mV, temperature coefficient of 7ppm∘C in the range of −40 to 125 °C, a power supply reje

Direct Continuous Time System Identification of MISO Transfer Function Models applied to Type 1 Diabetes

This paper shows an application of continuous-time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation exa

Exploiting Task Redundancy in Industrial Manipulators during Drilling Operations

A drilling task requires a mechanism with five degrees of freedom, in order to achieve the correct position and orientation of the drilling tool. When performed with a standard 6-axes industrial robot, this task leaves an extra degree of freedom that can be exploited in order to achieve any additional criterion. Unfortunately, typical industrial robotic control architectures do not allow the user