A Sensorless PMDC Motor Speed Controller with a Logical Overcurrent Protection

A method to control the speed or the torque of a permanent-magnet direct current motor is presented. The rotor speed and the external torque estimation are simultaneously provided by appropriate observers. The sensorless control scheme is based on current measurement and switching states of power devices. The observer’s performances are dependent on the accurate machine parameters knowledge. Sliding mode control approach was adopted for drive control, providing the suitable switching states to the chopper power devices. Despite the predictable chattering, a convenient first order switching function was considered enough to define the sliding surface and to correspond with the desired control specifications and drive performance. The experimental implementation was supported on a single dsPIC and the controller includes a logic overcurrent protection.

Adaptive mutations in bacteria: high rate and small effects

Evolution by natural selection is driven by the continuous generation of adaptive mutations. We measured the genomic mutation rate that generates beneficial mutations and their effects on fitness in Escherichia coli under conditions in which the effect of competition between lineages carrying different beneficial mutations is minimized. We found a rate on the order of 10–5 per genome per generation, which is 1000 times as high as previous estimates, and a mean selective advantage of 1%. Such a high rate of adaptive evolution has implications for the evolution of antibiotic resistance and pathogenicity.

An adaptive educational system for higher education

The main objective of an Adaptive System is to adequate its relation with the user (content presentation, navigation, interface, etc.) according to a predefined but updatable model of the user that reflects his objectives, preferences, knowledge and competences [Brusilovsky, 2001], [De Bra, 2004]. For Educational Adaptive Systems, the emphasis is placed on the student knowledge in the domain application and learning style, to allow him to reach the learning objectives proposed for his training [Chepegin, 2004]. In Educational AHS, the User Model (UM), or Student Model, has increased relevance: when the student reaches the objectives of the course, the system must be able to readapt, for example, to his knowledge [Brusilovsky, 2001]. Learning Styles are understood as something that intent to define models of how given person learns. Generally it is understood that each person has a Learning Style different and preferred with the objective of achieving better results. Some case studies have proposed that teachers should assess the learning styles of their students and adapt their classroom and methods to best fit each student's learning style [Kolb, 2005], [Martins, 2008]. The learning process must take into consideration the individual cognitive and emotional parts of the student. In summary each Student is unique so the Student personal progress must be monitored and teaching shoul not be not generalized and repetitive [Jonassen, 1991], [Martins, 2008]. The aim of this paper is to present an Educational Adaptive Hypermedia Tool based on Progressive Assessment.

User modeling In adaptive hypermedia educational systems

This document is a survey in the research area of User Modeling (UM) for the specific field of Adaptive Learning. The aims of this document are: To define what it is a User Model; To present existing and well known User Models; To analyze the existent standards related with UM; To compare existing systems. In the scientific area of User Modeling (UM), numerous research and developed systems already seem to promise good results, but some experimentation and implementation are still necessary to conclude about the utility of the UM. That is, the experimentation and implementation of these systems are still very scarce to determine the utility of some of the referred applications. At present, the Student Modeling research goes in the direction to make possible reuse a student model in different systems. The standards are more and more relevant for this effect, allowing systems communicate and to share data, components and structures, at syntax and semantic level, even if most of them still only allow syntax integration.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

EGNOS based virtual reference stations

We propose the use of the European Geostationary Navigation Overlay Service (EGNOS) data - real time on line data provided by SISNeT - to develop Virtual Reference Stations and, thus, increase the quality of the Position, Velocity an Time (PVT) solution of receivers unable to interface directly with EGNOS. A Virtual Reference Station (VRS) is a concept where the existence of a differential reference station located near a mobile rover is simulated by software in order to increase the accuracy of the PVT solution of the mobile GNSS receiver.

Parallel real-time support for distributed adaptive embedded applications

Real-time embedded applications require to process large amounts of data within small time windows. Parallelize and distribute workloads adaptively is suitable solution for computational demanding applications. The purpose of the Parallel Real-Time Framework for distributed adaptive embedded systems is to guarantee local and distributed processing of real-time applications. This work identifies some promising research directions for parallel/distributed real-time embedded applications.

Service offloading in adaptive real-time systems

Smartphones and other internet enabled devices are now common on our everyday life, thus unsurprisingly a current trend is to adapt desktop PC applications to execute on them. However, since most of these applications have quality of service (QoS) requirements, their execution on resource-constrained mobile devices presents several challenges. One solution to support more stringent applications is to offload some of the applications’ services to surrogate devices nearby. Therefore, in this paper, we propose an adaptable offloading mechanism which takes into account the QoS requirements of the application being executed (particularly its real-time requirements), whilst allowing offloading services to several surrogate nodes. We also present how the proposed computing model can be implemented in an Android environment

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.

The utilization bound of non-preemptive rate-monotonic scheduling in controller area networks is 25%

Consider a distributed computer system comprising many computer nodes, each interconnected with a controller area network (CAN) bus. We prove that if priorities to message streams are assigned using rate-monotonic (RM) and if the requested capacity of the CAN bus does not exceed 25% then all deadlines are met.

An IEEE 802.15.4 protocol implementation (in nesC/TinyOS): reference guide v1.0

This technical report is to provide a reference guide to the implementation of the IEEE 802.15.4 protocol in nesC/TinyOS for the MICAz motes. The implementation is provided as a tool that can be used to implement, test and evaluate the current functionalities defined in the protocol standard as well as to enable the development of functionalities not yet implemented and new add-ons to the protocol.

Self-adaptive combination of global tabu search and local search for nonlinear equations

Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

Visualizing non-linear control system performance by means of multidimensional scaling

This paper addresses the use of multidimensional scaling in the evaluation of controller performance. Several nonlinear systems are analyzed based on the closed loop time response under the action of a reference step input signal. Three alternative performance indices, based on the time response, Fourier analysis, and mutual information, are tested. The numerical experiments demonstrate the feasibility of the proposed methodology and motivate its extension for other performance measures and new classes of nonlinearities.

Resistance of Aedes aegypti to temephos and adaptive disadvantages

OBJECTIVE To evaluate the resistance of Aedes aegypti to temephos Fersol 1G (temephos 1% w/w) associated with the adaptive disadvantage of insect populations in the absence of selection pressure. METHODS A diagnostic dose of 0.28 mg a.i./L and doses between 0.28 mg a.i./L and 1.40 mg a.i./L were used. Vector populations collected between 2007 and 2008 in the city of Campina Grande, state of Paraíba, were evaluated. To evaluate competition in the absence of selection pressure, insect populations with initial frequencies of 20.0%, 40.0%, 60.0%, and 80.0% resistant individuals were produced and subjected to the diagnostic dose for two months. Evaluation of the development of aquatic and adult stages allowed comparison of the life cycles in susceptible and resistant populations and construction of fertility life tables. RESULTS No mortality was observed in Ae. aegypti populations subjected to the diagnostic dose of 0.28 mg a.i./L. The decreased mortality observed in populations containing 20.0%, 40.0%, 60.0%, and 80.0% resistant insects indicates that temephos resistance is unstable in the absence of selection pressure. A comparison of the life cycles indicated differences in the duration and viability of the larval phase, but no differences were observed in embryo development, sex ratio, adult longevity, and number of eggs per female. CONCLUSIONS The fertility life table results indicated that some populations had reproductive disadvantages compared with the susceptible population in the absence of selection pressure, indicating the presence of a fitness cost in populations resistant to temephos.