Hybrid Feedback Control Methods for Robust and Global Power Conversion

In this paper, the applicability and importance of hybrid system tools for the design of control algorithms for energy conversion in power systems is illustrated in two hybrid control designs, one pertaining to DC/DC conversion and the other to DC/AC inversion. In particular, the mathematical models considered consist of constrained switched differential equations/inclusions that include all possible modes of operation of the systems. Furthermore, the obtained models can be analyzed and their algorithms designed using hybrid system tools so as to attain key desired properties, such as stability, forward invariance, global convergence, and robustness. We argue that hybrid system tools provide a systematic approach for analysis and controller design of power systems. In particular, hybrid system tools usually leads to power quantities that have better performance and robustness to state perturbations. Furthermore, they provide guidelines on how to tune the controller parameters based on design requirements. These factors motivate the implementation of the proposed hybrid controllers in modern power conversion systems that use renewable energy sources. Simulations illustrating the main results and benchmark tests are included

A Bayesian Reflection on Surfaces

The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data), is presented.Comment: 34 pages, 1 figure, abbreviated versions presented: Bayesian Statistics, Valencia, Spain, 1998; Maximum Entropy and Bayesian Methods, Garching, Germany, 199

The Evolution of Ethnic Identity From Adolescence to Middle Adulthood: The Case of the Immigrant Second Generation

Through an analysis of qualitative interview and survey data, this study examines ethnic identity development from midadolescence to middle adulthood among a representative sample of immigrants’ children from Mexico, the Philippines, and other countries, who were followed for more than 20 years. Findings reveal that ethnic self-identity labels are more stable in adulthood than adolescence or the transition to adulthood, but the importance of ethnic identity diminishes, especially among those born abroad. Most prefer ethnic identity labels referencing their origin country, reflecting family ties and cultural attachments. However, some, mostly foreign-born, shift to ethnic self-identity labels exclusively related to their American experience, including panethnic labels in response to U.S. racialization. Only a few actively resist such labeling and claim nonhyphenated American identities. Overall, the findings reveal how diverse ethnic identity development patterns over the life course are shaped both by ancestral attachments and the imposition of existing U.S. racial structures

Protein connectivity in chemotaxis receptor complexes

The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET) measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures

Geospatial multi-criteria analysis for identifying high priority clean energy investment opportunities: A case study on land-use conflict in Bangladesh

Bangladesh is a globally important emerging economy with rapidly increasing energy demand. The Bangladeshi government's primary capacity expansion plan is to install 13.3 GW of new coal by 2021, including the 1.3 GW Rampal coal power plant to be developed in the Sundarbans. Inadequate geospatial and economic information on clean energy investment opportunities are often a significant barrier for policy makers. Our study helps fill this gap by applying a new method to assess energy investment opportunities, with focus on understanding land-use conflicts, particularly important in this context as Bangladesh is constrained on land for agriculture, human settlements, and ecological preservation. By extending a geospatial multi-criteria analysis model (MapRE) we analyze the cost of various renewable energy generation technologies based on resource availability and key siting criteria such as proximity to transmission and exclusion from steep slopes, dense settlements or ecologically sensitive areas. We find there is more utility-scale solar potential than previously estimated, which can be developed at lower costs than coal power and with minimal cropland tradeoff. We also find significant potential for decentralized roof-top solar in commercial and residential areas. Even with a conservative land use program that reserves maximum land for agriculture and human settlement, there is more renewable energy capacity than needed to support Bangladeshi growth. This study provides critical and timely information for capacity expansion planning in South Asia and demonstrates the use of geospatial models to support decision-making in data-limited contexts