Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Computational Intelligence and Complexity Measures for Chaotic Information Processing

This dissertation investigates the application of computational intelligence methods in the analysis of nonlinear chaotic systems in the framework of many known and newly designed complex systems. Parallel comparisons are made between these methods. This provides insight into the difficult challenges facing nonlinear systems characterization and aids in developing a generalized algorithm in computing algorithmic complexity measures, Lyapunov exponents, information dimension and topological entropy. These metrics are implemented to characterize the dynamic patterns of discrete and continuous systems. These metrics make it possible to distinguish order from disorder in these systems. Steps required for computing Lyapunov exponents with a reorthonormalization method and a group theory approach are formalized. Procedures for implementing computational algorithms are designed and numerical results for each system are presented. The advance-time sampling technique is designed to overcome the scarcity of phase space samples and the buffer overflow problem in algorithmic complexity measure estimation in slow dynamics feedback-controlled systems. It is proved analytically and tested numerically that for a quasiperiodic system like a Fibonacci map, complexity grows logarithmically with the evolutionary length of the data block. It is concluded that a normalized algorithmic complexity measure can be used as a system classifier. This quantity turns out to be one for random sequences and a non-zero value less than one for chaotic sequences. For periodic and quasi-periodic responses, as data strings grow their normalized complexity approaches zero, while a faster deceasing rate is observed for periodic responses. Algorithmic complexity analysis is performed on a class of certain rate convolutional encoders. The degree of diffusion in random-like patterns is measured. Simulation evidence indicates that algorithmic complexity associated with a particular class of 1/n-rate code increases with the increase of the encoder constraint length. This occurs in parallel with the increase of error correcting capacity of the decoder. Comparing groups of rate-1/n convolutional encoders, it is observed that as the encoder rate decreases from 1/2 to 1/7, the encoded data sequence manifests smaller algorithmic complexity with a larger free distance value

Stratégies de commande numérique pour un convertisseur DC/DC SEPIC en vue de l intégration

L utilisation des alimentations à découpage (SMPSs : switched mode power supplies) est à présent largement répandue dans des systèmes embarqués en raison de leur rendement. Les exigences technologiques de ces systèmes nécessitent simultanément une très bonne régulation de tension et une forte compacité des composants. SEPIC (Single-Ended Primary Inductor Converter) est un convertisseur à découpage DC/DC qui possède plusieurs avantages par rapport à d autres convertisseurs de structure classique. Du fait de son ordre élevé et de sa forte non linéarité, il reste encore peu exploité. L objectif de ce travail est d une part le développement des stratégies de commande performantes pour un convertisseur SEPIC et d autre part l implémentation efficace des algorithmes de commande développés pour des applications embarquées (FPGA, ASIC) où les contraintes de surface silicium et le facteur de réduction des pertes sont importantes. Pour ce faire, deux commandes non linéaires et deux observateurs augmentés (observateurs d état et de charge) sont exploités : une commande et un observateur fondés sur le principe de mode de glissement, une commande prédictive et un observateur de Kalman étendu. L implémentation des deux lois de commande et l observateur de Kalman étendu sont implémentés sur FPGA. Une modulation de largeur d impulsion (MLI) numérique à 11-bit de résolution a été développée en associant une technique de modulation - de 4-bit, un DCM (Digital Clock Management) segmenté et déphasé de 4-bit, et un compteur-comparateur de 3-bit. L ensemble des approches proposées sont validées expérimentalement et constitue une bonne base pour l intégration des convertisseurs à découpage dans les alimentations embarquées.The use of SMPS (Switched mode power supply) in embedded systems is continuously increasing. The technological requirements of these systems include simultaneously a very good voltage regulation and a strong compactness of components. SEPIC ( Single-Ended Primary Inductor Converter) is a DC/DC switching converter which possesses several advantages with regard to the other classical converters. Due to the difficulty in control of its 4th-order and non linear property, it is still not well-exploited. The objective of this work is the development of successful strategies of control for a SEPIC converter on one hand and on the other hand the effective implementation of the control algorithm developed for embedded applications (FPGA, ASIC) where the constraints of Silicon surface and the loss reduction factor are important. To do it, two non linear controls and two observers of states and load have been studied: a control and an observer based on the principle of sliding mode, a deadbeat predictive control and an Extended Kalman observer. The implementation of both control laws and the Extended Kalman observer are implemented in FPGA. An 11-bit digital PWM has been developed by combining a 4-bit - modulation, a 4-bit segmented DCM (Digital Clock Management) phase-shift and a 3-bit counter-comparator. All the proposed approaches are experimentally validated and constitute a good base for the integration of embedded switching mode convertersVILLEURBANNE-DOC'INSA-Bib. elec. (692669901) / SudocSudocFranceF

Modelling, Simulation and Data Analysis in Acoustical Problems

Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years