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A method to decompose a motion-planning problem into several segments is presented. It is based on a modification of the original problem, such that certain variables at the splitting points are considered to be precomputed and thus fixed and the remaining variables are obtained by performing Lagrange relaxation. The resulting dual problem is split into several subproblems, allowing parallel compu
A simplified combined-slip model that only considers the extreme case at the friction limit is suggested and used in a closed-loop controller for autonomous vehicle handling in at-the-limit maneuvers. In the development of the controller it is assumed that the front wheels are individually steered, but it is demonstrated in a left-hand turn scenario that with a simple adaptation, the method is sti
This paper presents a real-time hand gesture recognition system by accelerating a convolutional neural network (CNN) using FPGA platform. More specifically, ZynqNet is adopted and modified to fulfill the classification task of recognizing the Swedish manual alphabet, which is used by sign language users for spelling purposes, also known as fingerspelling. Data augmentation and transfer learning te
This paper presents a continuous-time ΔΣ ADC in a 28nm-FDSOI CMOS technology. The ADC is clocked at 5GHz with a signal bandwidth of 250 MHz, for an oversampling ratio (OSR) of only 10. The conversion from high-level model to circuit-level implementation requires multiple high-speed design methodologies and a careful layout. A 4th order loop filter is adopted to enhance quantization noise shaping i
In this paper, we study event-based PID control from an optimal stochastic control perspective. The purpose is to better understand what implementation features are critical for achieving good event-based PID performance. For this end, we formulate an LQG control design problem for a double integrator process with an integral disturbance, where the solution is an ideal PID controller. We then cons
Signals are physical variables or quantities measured at various parts of a system, which when processed yield the desired information. A wide variety of signals are often encountered in describing many practical systems. Electrical signal, in form of current and voltage, is the most easily measured quantity, hence the need to use sensors and transducers to transform other non-electrical quantity
Control systems can be vulnerable to security threats where an attacker gathers information about the execution of the system. In particular, side-channel attacks exploit the predictability of real-time control systems and of their schedules. To counteract their action, a scheduler can randomize the temporal execution of tasks and limit the amount of information the attacker can gather. Schedule r
Control theory has contributed a set of foundational techniques to handle "change" at runtime in software applications. These techniques however have fundamental limitations as well: (i) they require the development and understanding of mathematical models; (ii) synthesizing solutions is often done on a per-problem basis, discouraging flexibility and generality. Software engineering, as a discipli
Devices sharing a network compete for bandwidth, being able to transmit only a limited amount of data. This is for example the case with a network of cameras, that should record and transmit video streams to a monitor node for video surveillance. Adaptive cameras can reduce the quality of their video, thereby increasing the frame compression, to limit network congestion. In this paper, we exploit
A continuous-time, 65-nm CMOS, front-end for processing DNA sequencing measurements from biological nanopore sensors is presented. The measured design has an input referred noise floor of 8.5\;{\text{fA}}/\sqrt {{\text{Hz}}} for 100 pA DC current while consuming 10X less power. The chip also consists of an integrated ADC.
Interesting approaches to counteract performance variability within cloud datacenters include sending multiple request clones, either immediately or after a specified waiting time. In this paper we present a performance model of cloud applications that utilize the latter concept, known as speculative execution. We study the popular Join-Shortest-Queue load-balancing strategy under the processor sh
We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative ref
The VIVE lighthouse system is evaluated for indoor positioning of micro unmanned aerialcvehicles (MUAVs). A detailed mathematical analysis is provided, including a Cramer-Raocbound derivation and performance analysis of the MUAV state estimate. The lighthousecmeasurements are fused with inertial measurements in a multiplicative extended Kalmanfilter (MEKF). We consider two implementations, one w
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
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
This paper investigates the robustness of control systems when a controller is run in a Fog environment. Control systems in the Fog are introduced and a discussion regarding relevant faults is presented. A preliminary investigation of the robustness properties of a MinSeg case study is presented and commented. The discussion is then used to outline future lines of research.
Autonomous vehicle functions in safety-critical situations show promise in reducing the risk and saving lives in accidents compared to existing safety systems. Consequently, it is from many perspectives advantageous to be able to quantify the potential benefits of new autonomous systems for vehicle maneuvers at-the-limit of tire friction. Here, to estimate the potential in terms of saved lives and
Personalized patient care has gained increasing attention in recent years. Precise drug dosing is critical for patient safety and good clinical outcomes, especially in intensive care units, where patients often are in critical conditions. Such treatments can include stabilizing blood pressure and heart rate or maintaining safe anesthesia levels. However, the inter-patient variability in the drug r
Purpose: The survival rate of breast cancer for women in low- and middle-income countries is poor compared with that in high-income countries. Point-of-care ultrasound (POCUS) combined with deep learning could potentially be a suitable solution enabling early detection of breast cancer. We aim to improve a classification network dedicated to classifying POCUS images by comparing different techniqu
