New developments in mathematical control and information for fuzzy systems

Hamid Reza Karimi, Mohammed Chadli and Peng Sh

Model predictive satisficing fuzzy logic control,”

Abstract-Model-predictive control, which is an alternative to conventional optimal control, provides controller solutions to many constrained and nonlinear control problems. However, even when a good model is available, it may be necessary for an expert to specify the relationship between local model predictions and global system performance. We present a satisficing fuzzy logic controller that is based on a receding control horizon, but which employs a fuzzy description of system consequences via model predictions. This controller considers the gains and losses associated with each control action, is compatible with robust design objectives, and permits flexible defuzzifier design. We demonstrate the controller's application to representative problems from the control of uncertain nonlinear systems

Global Catastrophic Nuclear Risk: A Guide for Philanthropists

Nuclear weapons are a global catastrophic risk; a nuclear war could kill untold millions, inflict horrific suffering on survivors, and derail human civilization as we know it. This report forms a guide for philanthropists who seek to mitigate this risk and maximize the counterfactual impact of their charitable donations. Specifically, the report seeks to guide funders entering this field in the wake of several challenges: the apparent collapse of post-Cold War arms control, the second year of the Russo-Ukrainian War, rising U.S.-China tensions, and a large funding shortfall for nuclear security. It mirrors many of the themes of Founders Pledge's Guide to the Changing Landscape of High-Impact Climate Philanthropy, and is indebted to the insights in that document. The report's analysis has four steps:Understanding key features of the landscape of nuclear philanthropy, with special attention to recent funding shortfalls. Analyzing the structure of the problem, emphasizing the super-linearity of expected costs; not all nuclear wars are equal, and bigger nuclear wars could be disproportionately more damaging than smaller nuclear wars for both current generations and the long-term future. Sketching guiding principles for nuclear philanthropy based on these ideas:Prioritize minimizing expected global war damage;Prioritize neglected strategies;Multiply impact by shaping great power behavior;Exercise leverage via policy advocacy;Pursue a strategy of "robust diversification."       4. Exploring practical implications of these principles. The section briefly describes               concrete projects that philanthropists can support. A conclusion enumerates key               uncertainties and sketches a path forward for philanthropists

Topology optimization for energy problems

The optimal design of energy systems is a challenge due to the large design space and the complexity of the tightly-coupled multi-physics phenomena involved. Standard design methods consider a reduced design space, which heavily constrains the final geometry, suppressing the emergence of design trends. On the other hand, advanced design methods are often applied to academic examples with reduced physics complexity that seldom provide guidelines for real-world applications. This dissertation offers a systematic framework for the optimal design of energy systems by coupling detailed physical analysis and topology optimization. Contributions entail both method-related and application-oriented innovations. The method-related advances stem from the modification of topology optimization approaches in order to make practical improvements to selected energy systems. We develop optimization models that respond to realistic design needs, analysis models that consider full physics complexity and design models that allow dramatic design changes, avoiding convergence to unsatisfactory local minima and retaining analysis stability. The application-oriented advances comprise the identification of novel optimized geometries that largely outperform industrial solutions. A thorough analysis of these configurations gives insights into the relationship between design and physics, revealing unexplored design trends and suggesting useful guidelines for practitioners. Three different problems along the energy chain are tackled. The first one concerns thermal storage with latent heat units. The topology of mono-scale and multi-scale conducting structures is optimized using both density-based and level-set descriptions. The system response is predicted through a transient conjugate heat transfer model that accounts for phase change and natural convection. The optimization results yield a large acceleration of charge and discharge dynamics through three-dimensional geometries, specific convective features and optimized assemblies of periodic cellular materials. The second problem regards energy distribution with district heating networks. A fully deterministic robust design model and an adjoint-based control model are proposed, both coupled to a thermal and fluid-dynamic analysis framework constructed using a graph representation of the network. The numerical results demonstrate an increased resilience of the infrastructure thanks to particular connectivity layouts and its rapidity in handling mechanical failures. Finally, energy conversion with proton exchange membrane fuel cells is considered. An analysis model is developed that considers fluid flow, chemical species transport and electrochemistry and accounts for geometry modifications through a density-based description. The optimization results consist of intricate flow field layouts that promote both the efficiency and durability of the cell

Développement d'un système de différenciation modulable par la lumière pour la création et le contrôle de consortiums microbiens dans S. cerevisiae, sa caractérisation en cellule unique pour le développement de modèles prédictifs, et son utilisation pour l'expression hétérologue

Les consortiums microbiens artificiels cherchent à exploiter la division du travail pour optimiser des fonctions et possèdent un immense potentiel pour la bioproduction. Les approches de co-culture, le mode préférentiel pour générer des consortiums, restent limitées dans leur capacité à donner naissance à des consortiums stables ayant des compositions précisément ajustées. J'ai développé ici un système de différenciation artificielle dans la levure boulanger capable de générer à partir d'une seule souche des consortiums microbiens stables avec des fonctionnalités choisies et ayant une composition définie par l'utilisateur dans l'espace et dans le temps, grâce à une modification génétique pilotée par optogénétique. Grâce à une dynamique rapide, reproductible et ajustable par la lumière, mon système permet un contrôle dynamique de la composition des consortiums dans des cultures continues pendant de longues périodes. Je démontre également que notre système peut être étendu de manière simple pour donner naissance à des consortiums avec de multiples sous-populations. Cette stratégie de différenciation artificielle établit un nouveau paradigme pour la création de consortiums microbiens complexes qui sont simples à mettre en oeuvre, contrôlables avec précision et polyvalents à utiliser.En plus de cela, j'ai caractérisé le système au niveau de la cellule unique dans différents contextes en changeant la structure du bruit du facteur de transcription optogénétique qui induit la différenciation. J'ai découvert que le changement de la structure du bruit introduisait un couplage complexe entre les niveaux de la population de cellule et des cellules individuelles, qui ne peut être prédit par un simple modèle d'équations différentielles ordinaires. L'utilisation d'un modèle stochastique bien caractérisé a permis de rétablir la prévisibilité.Enfin, j'ai couplé le système de différenciation avec un system d'arrêt de croissance et de bioproduction de sorte que les cellules différenciées arrêtent de croître et commencent à produire une protéine d'intérêt. J'ai comparé l'efficacité de l'approche basée sur la différenciation avec des équivalents constitutifs et inductibles. J'ai constaté que la production n'était pas monotone par rapport à la fraction de différenciation mais qu'elle pouvait surpasser l'expression induite par un promoteur constitutif fort.Artificial microbial consortia seek to leverage division-of-labour to optimize function and possess immense potential for bioproduction. Co-culturing approaches, the preferred mode of generating a consortium, remain limited in their ability to give rise to stable consortia having finely tuned compositions. Here, I developed an artificial differentiation system in budding yeast capable of generating stable microbial consortia with custom functionalities from a single strain at user-defined composition in space and in time based on optogenetically-driven genetic rewiring. Owing to fast, reproducible, and light-tunable dynamics, my system enables dynamic control of consortia composition in continuous cultures for extended periods independently of the cell density. I further demonstrate that our system can be extended in a straightforward manner to give rise to consortia with multiple subpopulations. This artificial differentiation strategy establishes a novel paradigm for the creation of complex microbial consortia that are simple to implement, precisely controllable, and versatile to use.In addition to this, I characterized the system at the single cell level in different genetic contexts by changing the noise structure of the optogenetic transcription factor that drives differentiation. I found that changing the noise structure introduced complex coupling between the population and the single cell level, which cannot be predicted by a simple population model. A stochastic model of differentiation composed in a stochastic model of plasmid fluctuations not only restored predictability, but revealed mechanistic insights into the functioning of the system. The latter was exploited to demonstrate control of expression of a constitutively expressed gene (proxy for plasmid copy number).Lastly, I coupled the differentiation system with a growth arrest and production module such that differentiated cells stop growing and start producing a protein of interest. Growth arrest was effected via hijacking of the mating pheromone pathway and production was carried out by an orthogonal transcription factor. I developed a light inducible reference to assess the increase in production upon growth arrest. Comparing the efficiency of the differentiation-based approach with constitutive and inducible counterparts, I found that production was non-monotonic with respect to differentiation fraction and could outcompete constitutive expression. However, production did not increase upon growth arrest

Power Converters in Power Electronics

In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters

Unbalance and Resonance Elimination on General Rotors with Active Bearings

Rotating machinery has a subtle, but profound impact on contemporary societies. Many modern achievements owe their existence to these machines, ranging from electrical power, cars, airplanes, to rockets. In these machines, rotor unbalances cause vibrations and stresses, decreasing their lifetime and leading to noise pollution. For decades, balancing and damping were the only methods to reduce these vibrations. The introduction of active magnetic bearings enabled new possibilities for rotor vibration reduction. Sophisticated control algorithms do not only allow for a reduction, but for a complete elimination of bearing forces caused by unbalances. Still, the existing methods suffer from drawbacks, including unclear behavior in rotor resonances, and poor stability. The invention of active bearings based on piezoactuators complicated the situation further: depending on the researcher’s background, contradicting methods are used for vibration reduction, resulting in an unclear and fragmented problem understanding. This work strives to resolve the apparent contradictions and drawbacks of the currently available methods to eliminate unbalances, generating a unified Problem solution for different active bearing technologies. After a careful Revision of the JEFFCOTT rotor, a new control approach is suggested. The latter does not only eliminate the rotor’s unbalance forces, but also the rotor’s resonance. The approach is extended to cover rotors with arbitrary mass, stiffness, damping and gyroscopic properties. A general, analytic solution indicates that the proposed control algorithm allows for a complete elimination of bearing forces and two rotor resonances. This is possible even when the rotor is attached to an arbitrary, flexible structure. The theoretical considerations allow for a derivation of control strategies for different actuator principles, technologies and arrangements, resulting in a consistent problem treatment and understanding. Actuator dimensioning Guidelines enable an effortless practical realization. This work introduces a new stability theorem for arbitrary mechanical Systems with collocated controllers. The theorem is subsequently applied to proof the controller’s superior stability properties, resulting in unconditional stability for general rotors

Towards UAV-assisted monitoring of onshore geological CO2 storage site

Scientists all over the world look for solutions to reduce greenhouse gas emissions in an effort to achieve proclaimed emissions reduction targets. An intriguing candidate with the potential to make a substantial contribution to this attempt is carbon capture and storage (CCS). The key advantage of CCS is that it provides the possibility to make a significant impact on the reduction of anthropogenic carbon dioxide (CO2) emissions from power plants and carbon-rich industry processes while maintaining existing fossil fuel energy infrastructure. The technique could therefore be used as a transitional solution until fossil fuels can be eliminated from the energy generation mix, and the energy efficiency of industrial processes as well as appliances and products is further improved. Like other technologies, CCS comes with its risks and rewards. To minimize possible negative impacts on humans as well as on the environment, it is necessary to understand the risks and to address them accordingly. A range of monitoring solutions for geological CO2 storage sites is available. However, a cost-effective solution for the regular observation of atmospheric CO2 concentrations (or tracer concentrations) of large areas above onshore geological CO2 storage sites has yet to be developed. This thesis discusses the use of a helicopter unmanned aerial vehicle (UAV) to fill this gap. The robot platform and its autopilot are designed to cope with ongoing sensor developments in addition to providing safety features necessary for the beyond line-of-sight operation of the UAV. The design focuses on the use of commercial off-the-shelf components for the aerial platform in order to shorten the development time and to reduce costs. The autopilot does neither enforce a specific helicopter model nor defines a set position estimation unit to be used. Access to the control loop enables low-level extensions like obstacle avoidance to be implemented. The developed solution allows the monitoring of an area of approximately 750m2 with one set of batteries in one altitude with a spatial resolution of 2m by 2m. Experiments show that point source leaks of as low as 100kg CO2 per day can be detected and their source located. As opposed to autonomous take-offs of the helicopter UAV, autonomous landings on small dedicated helipads require an accurate localization system. A time difference of arrival (TDOA) based acoustic localization system which is based on planar microphone arrays with at least four microphones is proposed. The system can be embedded into the landing platform and provides the accuracy necessary to land the UAV on a helipad of the size of 1m by 1m. A review of existing TDOA-based approaches is given. Simulations show that the developed approach outperforms its direct competitors for the targeted task. Furthermore, experimental results with the developed UAV confirm the feasibility of the introduced method. The effects of the sensor arrangement onto the quality of the calculated position estimates are also discussed. In order to combine robotic-assisted monitoring solutions and other monitoring strategies (e.g. sensor networks and individual sensors) into a single solution, it is necessary to have a framework which allows next to the measurement data analysis also the management (path changes, robot behavior changes, monitoring of internal robot state) of possibly multiple heterogeneous mobile robotic systems. A modular user interface (UI) framework is proposed which allows robots from different vendors and with various configurations next to individual sensors and sensor networks to be managed from a single application. The software system introduces a strict separation between the robot control software and UIs. UI implementations inside the UI framework can be reused across robot platforms, which can reduce the integration time of new robots significantly. The end user benefits by being able to manage a fleet of robots from various vendors and being able to analyze all the measurement data together in a single solution