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In this thesis, we draw inspiration from both classical system identification and modern machine learning in order to solve estimation problems for real-world, physical systems. The main approach to estimation and learning adopted is optimization based. Concepts such as regularization will be utilized for encoding of prior knowledge and basis-function expansions will be used to add nonlinear model
Friction stir welding (FSW) is a solid-state welding process where metals are joined without melting. Heat is generated by friction between a rotating non-consumable tool and the work-piece material, and by mechanical deformation of the material. The process, invented in 1991, provides several benefits over arc welding and other fusion processes: No filler material has to be added, low energy cons
In this chapter, we discuss the open challenges in building self-aware computing systems that are still being faced by the research and development community. The challenges can be theoretical, technical, computational, or even sociological. First, we highlight the challenges associated with each of the earlier parts of the book and summarize on respective future research directions. We then offer
We present an accurate analysis of phase noise in ring oscillators, where each stage in the ring is a CMOS inverter loaded by a capacitance. Closed-form phase noise expressions are obtained in both 1/f2 and 1/f3 offset frequency regions, displaying an excellent agreement with numerical simulations using either ideal Verilog-A MOS models (allowing theoretical predictions to be tested with exactly t
This work considers the assignment of vehicle traffic consisting of both individual, opportunistic vehicles and a cooperative fleet of vehicles. The first set of vehicles seek a user-optimal policy and the second set seeks a fleet-optimal policy. We provide explicit sufficient conditions for the existence and uniqueness of a Nash equilibrium at which both policies are satisfied.We also propose two
The Large Gain Theorem is an input-output stability result with intriguing applications in the field of control systems. This paper aims to increase understanding and appreciation of the Large Gain Theorem by presenting an interpretation of it for linear time-invariant systems using the well-known Nyquist stability criterion and illustrative examples of its use. The Large Gain Theorem is complemen
Due to their wide adaptability to different application fields spanning from opinion dynamics to biology, the analysis of evolutionary dynamics is a compelling problem in the science of networks and systems. In this paper, we deal with controlled evolutionary dynamics in networks. We discuss a novel approach to model these phenomena, which enables us to estimate the duration of the process dependi
This paper describes a frequency generator supporting over-an-octave tuning range for 5G receiver front-end. Generator is built by composition of smaller-range oscillators multiplexed to the common output that drives a downconversion mixer. Simulated in 28nm CMOS with full physical device models the composite oscillator exhibits a frequency tuning range from 21.5 to 60.7GHz (95.3%) dissipating les
In this tutorial paper we first present some foundational results regarding the theory of positive systems. In particular, we present fundamental results regarding stability, positive realization and positive stabilization by means of state feedback. Special attention is also paid to the system performance in terms of disturbance attenuation. Under the asymptotic stability assumption, such perform
A performance-based approach is developed for adaptive robust control of linear systems with uncertain parameters. The dual control objective involves the disturbance attenuation and worst case identification of the unknown parameters. The proposed synthesis procedure relies on sufficient conditions, given in terms of suitable solutions of perturbed differential Riccati equations to exist. Althoug
Optimization problems with rank constraints appear in many diverse fields such as control, machine learning, and image analysis. Since the rank constraint is nonconvex, these problems are often approximately solved via convex relaxations. Nuclear norm regularization is the prevailing convexifying technique for dealing with these types of problem. This paper introduces a family of low-rank inducing
Objective: The goal of this study was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness.Methods: We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce
This paper presents a scalable and high-Throughput hybrid computing platform for the real-Time multi-particle based Linac (Linear accelerator) simulation model to be used at the European Spallation Source (ESS). The multi-particle simulation model with non-linear modeling is needed to provide a realistic behavior of the particle beam for reducing the losses at the superconducting structures. The c
This paper presents a cryptographic processor compliant with the security algorithms specified by the 3rd Generation Partnership Project (3GPP) specifications for Long Term Evolution (LTE). The proposed processor has been adapted to the needs of the low end portfolio technologies that compose the Internet of Things (IoT) market, which addresses low-Area, low-cost and low-data rate applications. Th
We consider model order reduction of stable linear systems which leave ellipsoidal cones invariant. We show how balanced truncation can be modified to preserve cone- invariance. Additionally, this implies a method to perform external positivity preserving model reduction for a large class of systems.
Industrial robots typically require detailed programming and carefully configured work cells to perform well. The large engineering effort implicates high cost and long preparation time, and this is the major obstruction when mediating tasks to robots. The research in this thesis therefore aims to make robot programming faster and more accessible. Methods that allow for programmers to mediate and
This document outlines how to setup and run computations in parallel using Julia on a collection of remote computers, such as computers in a university lab. After the environment has been setup,Only minor modifications to serially executed code is necessary to enable parallel execution.Written for Julia version 1.0
