Nonlinear normal modes in mechanical systems: concept and computation with numerical continuation

The purpose of this Project is, first and foremost, to disclose the topic of nonlinear vibrations and oscillations in mechanical systems and, namely, nonlinear normal modes NNMs to a greater audience of researchers and technicians. To do so, first of all, the dynamical behavior and properties of nonlinear mechanical systems is outlined from the analysis of a pair of exemplary models with the harmonic balanced method. The conclusions drawn are contrasted with the Linear Vibration Theory. Then, it is argued how the nonlinear normal modes could, in spite of their limitations, predict the frequency response of a mechanical system. After discussing those introductory concepts, I present a Matlab package called 'NNMcont' developed by a group of researchers from the University of Liege. This package allows the analysis of nonlinear normal modes of vibration in a range of mechanical systems as extensions of the linear modes. This package relies on numerical methods and a 'continuation algorithm' for the computation of the nonlinear normal modes of a conservative mechanical system. In order to prove its functionality, a two degrees of freedom mechanical system with elastic nonlinearities is analized. This model comprises a mass suspended on a foundation by means of a spring-viscous damper mechanism -analogous to a very simplified model of most suspended structures and machines- that has attached a mass damper as a passive vibration control system. The results of the computation are displayed on frequency energy plots showing the NNMs branches along with modal curves and time-series plots for each normal mode. Finally, a critical analysis of the results obtained is carried out with an eye on devising what they can tell the researcher about the dynamical properties of the system.

Development of a fuzzy control based self-adaptive system for energy saving in constrained networks for the Internet of Things

Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.

A Wireless Charging System Applying Phase-Shift and Amplitude Control to Maximize Efficiency and Extractable Power

Wireless power transfer (WPT) is an emerging technology with an increasing number of potential applications to transfer power from a transmitter to a mobile receiver over a relatively large air gap. However, its widespread application is hampered due to the relatively low efficiency of current Wireless power transfer (WPT) systems. This study presents a concept to maximize the efficiency as well as to increase the amount of extractable power of a WPT system operating in nonresonant operation. The proposed method is based on actively modifying the equivalent secondary-side load impedance by controlling the phase-shift of the active rectifier and its output voltage level. The presented hardware prototype represents a complete wireless charging system, including a dc-dc converter which is used to charge a battery at the output of the system. Experimental results are shown for the proposed concept in comparison to a conventional synchronous rectification approach. The presented optimization method clearly outperforms state-of-the-art solutions in terms of efficiency and extractable power.

A global two component signal transduction system that integrates the control of photosynthesis, carbon dioxide assimilation, and nitrogen fixation

Photosynthesis, biological nitrogen fixation, and carbon dioxide assimilation are three fundamental biological processes catalyzed by photosynthetic bacteria. In the present study, it is shown that mutant strains of the nonsulfur purple photosynthetic bacteria Rhodospirillum rubrum and Rhodobacter sphaeroides, containing a blockage in the primary CO2 assimilatory pathway, derepress the synthesis of components of the nitrogen fixation enzyme complex and abrogate normal control mechanisms. The absence of the Calvin–Benson–Bassham (CBB) reductive pentose phosphate CO2 fixation pathway removes an important route for the dissipation of excess reducing power. Thus, the mutant strains develop alternative means to remove these reducing equivalents, resulting in the synthesis of large amounts of nitrogenase even in the presence of ammonia. This response is under the control of a global two-component signal transduction system previously found to regulate photosystem biosynthesis and the transcription of genes required for CO2 fixation through the CBB pathway and alternative routes. In addition, this two-component system directly controls the ability of these bacteria to grow under nitrogen-fixing conditions. These results indicate that there is a molecular link between the CBB and nitrogen fixation process, allowing the cell to overcome powerful control mechanisms to remove excess reducing power generated by photosynthesis and carbon metabolism. Furthermore, these results suggest that the two-component system integrates the expression of genes required for the three processes of photosynthesis, nitrogen fixation, and carbon dioxide fixation.

Creation of a reversible on/off system for site-specific in vivo control of exogenous gene activity in the renal glomerulus.

Using genetically engineered glomerular mesangial cells, an in vivo gene transfer approach was developed that specifically targets the renal glomerulus. By combining this system with a tetracycline (Tc)-responsive promoter, the present study aimed to create a reversible on/off system for site-specific in vivo control of exogenous gene activity within the glomerulus. In the Tc regulatory system, a Tc-controlled transactivator (tTA) encoded by a regulator plasmid induces target gene transcription by binding to a tTA-responsive promoter located in a response plasmid. Tc inhibits this tTA-dependent transactivation via its affinity for tTA. In double-transfected cells, therefore, the activity of a transgene can be controlled by Tc. Cultured rat mesangial cells were cotransfected with a regulator plasmid and a response plasmid that introduces a beta-galactosidase gene. In vitro, stable double-transfectant MtTAG cells exhibited no beta-galactosidase activity in the presence of Tc. However, following withdrawal of Tc from culture media, expression of beta-galactosidase was induced within 24 h. When Tc was again added, the expression was rapidly resuppressed. Low concentrations of Tc were sufficient to maintain the silent state of tTA-dependent promoter. MtTAG cells were then transferred into the rat glomeruli via renal artery injection. In the isolated chimeric glomeruli, expression of beta-galactosidase was induced ex vivo in the absence of Tc, whereas it was repressed in its presence. When Tc-pretreated MtTAG cells were transferred into the glomeruli of untreated rats, beta-galactosidase expression was induced in vivo within 3 days. Oral administration of Tc dramatically suppressed this induction. These data demonstrate the feasibility of using mesangial cell vectors combined with the Tc regulatory system for site-specific in vivo control of exogenous gene expression in the glomerulus.

MEGARA control system

MEGARA (Multi-Espectrografo en GTC de Alta Resolucion para Astronomia) is an optical Integral-Field Unit (IFU) and Multi-Object Spectrograph (MOS) designed for the GTC 10.4 m telescope in La Palma. The MEGARA Control System will provide the capabilities to move the different mechanisms of the instrument, to readout the data from the detector controller and the necessary routines for the Inspector Panels, the MEGARA Observing Preparation Software Suite, the Data Factory and the Sequencer strategies.

Algebraic derivative estimation applied to nonlinear control of magnetic levitation.

The subject of this thesis is the real-time implementation of algebraic derivative estimators as observers in nonlinear control of magnetic levitation systems. These estimators are based on operational calculus and implemented as FIR filters, resulting on a feasible real-time implementation. The algebraic method provide a fast, non-asymptotic state estimation. For the magnetic levitation systems, the algebraic estimators may replace the standard asymptotic observers assuring very good performance and robustness. To validate the estimators as observers in closed-loop control, several nonlinear controllers are proposed and implemented in a experimental magnetic levitation prototype. The results show an excellent performance of the proposed control laws together with the algebraic estimators.

System for robot control inspired by the functionality and organisation of the human nervous system

This paper presents a model of a control system for robot systems inspired by the functionality and organisation of human neuroregulatory system. Our model was specified using software agents within a formal framework and implemented through Web Services. This approach allows the implementation of the control logic of a robot system with relative ease, in an incremental way, using the addition of new control centres to the system as its behaviour is observed or needs to be detailed with greater precision, without the need to modify existing functionality. The tests performed verify that the proposed model has the general characteristics of biological systems together with the desirable features of software, such as robustness, flexibility, reuse and decoupling.

Multi-agent system for control of robots inspired on the distributed activity and hormonal regulation of humans

Robotics is an emerging field with great activity. Robotics is a field that presents several problems because it depends on a large number of disciplines, technologies, devices and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges. New uses are, for example, household robots or professional robots. To facilitate the low cost, rapid development of robotic systems, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems. Specifically, we model the decentralized activity and hormonal variation.

Decomposition of human behavior using model of competencies: application to robotic control system

For many years, humans and machines have shared the same physical space. To facilitate their interaction with humans, their social integration and for more rational behavior has been sought that the robots demonstrate human-like behavior. For this it is necessary to understand how human behavior is generated, discuss what tasks are performed and how relate to themselves, for subsequent implementation in robots. In this paper, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this work has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

Model of Competencies for Decomposition of Human Behavior: Application to Control System of Robots

Humans and machines have shared the same physical space for many years. To share the same space, we want the robots to behave like human beings. This will facilitate their social integration, their interaction with humans and create an intelligent behavior. To achieve this goal, we need to understand how human behavior is generated, analyze tasks running our nerves and how they relate to them. Then and only then can we implement these mechanisms in robotic beings. In this study, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this study has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

Efficiency of a conductive cement-based anodic system for the application of cathodic protection, cathodic prevention and electrochemical chloride extraction to control corrosion in reinforced concrete structures

This article describes the research carried out regarding the application of cathodic protection (CP) and cathodic prevention (CPrev), in some cases with a pre-treatment of electrochemical chloride extraction (ECE), on representative specimens of reinforced concrete structures, using an anodic system consisting of a graphite-cement paste applied as a coating on the surface. The aim of this research is to find out the competence of this anode for the aforementioned electrochemical treatments. The efficiency of this anode has been clearly demonstrated, as well as its capability to apply a combined process of ECE and after CP.

Fuzzy control of a water pump for an agricultural plant growth system

At the present time there is a high pressure toward the improvement of all the production processes. Those improvements can be sensed in several directions in particular those that involve energy efficiency. The definition of tight energy efficiency improvement policies is transversal to several operational areas ranging from industry to public services. As can be expected, agricultural processes are not immune to this tendency. This statement takes more severe contours when dealing with indoor productions where it is required to artificially control the climate inside the building or a partial growing zone. Regarding the latter, this paper presents an innovative system that improves energy efficiency of a trees growing platform. This new system requires the control of both a water pump and a gas heating system based on information provided by an array of sensors. In order to do this, a multi-input, multi-output regulator was implemented by means of a Fuzzy logic control strategy. Presented results show that it is possible to simultaneously keep track of the desired growing temperature set-point while maintaining actuators stress within an acceptable range.