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Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applicationsin e.g networked control systems (NCS). However, the problem of designing an optimal event-based state estimator often becomes untractable due to nonlinear measurements. This complexity is avoided with stochastic event-triggering. In this work, we

We consider the problem of localizing a novel image in a large 3D model, given that the gravitational vector is known. In principle, this is just an instance of camera pose estimation, but the scale of the problem introduces some interesting challenges. Most importantly, it makes the correspondence problem very difficult so there will often be a significant number of outliers to handle. To tackle

Algorithms for secure encryption in a post-quantum world are currently receiving a lot of attention in the research community, including several larger projects and a standardization effort from NIST. One of the most promising algorithms is the code-based scheme called QC-MDPC, which has excellent performance and a small public key size. In this work we present a very efficient key recovery attack

In computer vision, many problems can be formulated as finding a low rank approximation of a given matrix. Ideally, if all elements of the measurement matrix are available, this is easily solved in the L2-norm using factorization. However, in practice this is rarely the case. Lately, this problem has been addressed using different approaches, one is to replace the rank term by the convex nuclear no

Many modern software applications have performance requirements, like mobile and embedded systems that must keep up with sensor data, or web services that must return results to users within an acceptable latency bound. For such applications, the goal is not to run as fast as possible, but to meet their performance requirements with minimal resource usage, the key resource in most systems being en

Mathematical optimization is becoming increasingly important for engineering in general and control in particular. This thesis deals with numerical methods, primarily direct collocation, and symbolic methods, primarily block-triangular ordering and tearing, for numerical solution of general dynamic optimization problems involving dynamical systems modeled by large-scale differential-algebraic equa

We present the PalCom Object Notation, a textual data representation format for communication between internet of things which support binary and textual data. The format does not require parsing of user data (or the “payload”) and is thus efficient to use also for large binary values such as digital images, audio and video as well as for short textual values. These can be mixed in the same messag

We propose a novel approach to the problem of inverse kinematics for possibly redundant planar manipulators. We show that, by considering the joints as point masses in a fictitious gravity field, and by adding proper constraints to take into account the length of the links, the kinematic inversion may be cast as a convex programming problem. Convex constraints in the decision variables (in particu

The problem of synthesizing network-decentralized observers arises when several agents, corresponding to the nodes of a network, exchange information about local measurements to asymptotically estimate their own state. The network topology is unknown to the nodes, which can rely on information about their neighboring nodes only. For homogeneous systems, composed of identical agents, we show that a

We address H-infinity state feedback and give a simple form for an optimal control law applicable to linear time invariant systems with symmetric and Hurwitz state matrix. More specifically, the control law as well as the minimal value of the norm can be expressed in the matrices of the system's state space representation, given separate cost on state and control input. Thus, the control law is tr

This paper considers switching output feedback control of linear systems and variable-structure systems. Theory for stability analysis and design for a class of observer-based feedback control systems is presented. A circle-criterion approach can be used to design an observer-based state feedback control which yields a closed-loop system with specified robustness characteristics. The approach is r

In this paper we show how to build an economically optimal feedback control strategy for the re-dispatch of electricity generation. We assume that the operator steers production in a set of controllable power plants by altering the active power set-point of each generator, within a set of predefined set-points. The operators strategy will be based on balancing the operating cost against the expect

Harmonic task scheduling has many attractive properties, including a utilization bound of 100% under rate-monotonic scheduling and reduced jitter. At the same time, it places a severe constraint on the task period assignment for any application. In this paper, we explore the use of harmonic task scheduling for applications with multiple feedback control tasks. We present an algorithm for finding h

This contribution reviews theory, algorithms, and validation results for system identification of continuous-time models from finite non-uniformly sampled input-output sequences. The algorithms developed are autoregressive methods, and methods of stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model and a stochastic innovati

We consider the problem of tool position and orientation state estimation for robot manipulators in workspace by sensor fusion of the internal robot joint measurements with inertial measurement unit data. A prerequisite for this to be successful is accurate calibration of the sensors used. Therefore, we discuss a method for calibration of the sensor with respect to the robot end-effector, which is

Recently, several convergence rate results for Douglas-Rachford splitting and the alternating direction method of multipliers (ADMM) have been presented in the literature. In this paper, we show global linear convergence rate bounds for Douglas-Rachford splitting and ADMM under strong convexity and smoothness assumptions. We further show that the rate bounds are tight for the class of problems und

Robust performance of networks of interconnected heterogenous nonlinear dynamic systems is studied using the theory of integral quadratic constraints. By appealing to recent results on chordal sparsity decompositions of rational transfer matrices, distributed and scalable certificates for performance of interconnections are proposed. The approach is more direct since it does not involve reformulat

Perturbation problems for operators with embedded eigenvalues are generally challenging since the embedded eigenvalues cannot be separated from the rest of the spectrum. In this paper, we study a perturbation problem for embedded eigenvalues for a magnetic Schrödinger operator, when the underlying domain is a cylinder. The magnetic potential is C2 with an algebraic decay rate as the unbounded vari