Multimodeling Control via System Balancing

A new approach in multimodeling strategy is proposed. Multimodel strategies in which control agents use different simplified models of the same system are being developed using balancing transformation and the corresponding order reduction concepts. Traditionally, the multimodeling concept was studied using the ideas of multitime scales (singular perturbations) and weak subsystem coupling. For all reduced-order models obtained, a Linear Quadratic Gaussian (LQG) control problem was solved. Different order reduction techniques were compared based on the values of the optimized criteria for the closed-loop case where the full-order balanced model utilizes regulators calculated to be the optimal for various reduced-order models. The results obtained were demonstrated on a real-world example: a multiarea power system consisting of two identical areas, that is, two identical power plants

Category Theory and Model-Driven Engineering: From Formal Semantics to Design Patterns and Beyond

There is a hidden intrigue in the title. CT is one of the most abstract mathematical disciplines, sometimes nicknamed "abstract nonsense". MDE is a recent trend in software development, industrially supported by standards, tools, and the status of a new "silver bullet". Surprisingly, categorical patterns turn out to be directly applicable to mathematical modeling of structures appearing in everyday MDE practice. Model merging, transformation, synchronization, and other important model management scenarios can be seen as executions of categorical specifications. Moreover, the paper aims to elucidate a claim that relationships between CT and MDE are more complex and richer than is normally assumed for "applied mathematics". CT provides a toolbox of design patterns and structural principles of real practical value for MDE. We will present examples of how an elementary categorical arrangement of a model management scenario reveals deficiencies in the architecture of modern tools automating the scenario.Comment: In Proceedings ACCAT 2012, arXiv:1208.430

Tools of the Trade: A Survey of Various Agent Based Modeling Platforms

Agent Based Modeling (ABM) toolkits are as diverse as the community of people who use them. With so many toolkits available, the choice of which one is best suited for a project is left to word of mouth, past experiences in using particular toolkits and toolkit publicity. This is especially troublesome for projects that require specialization. Rather than using toolkits that are the most publicized but are designed for general projects, using this paper, one will be able to choose a toolkit that already exists and that may be built especially for one's particular domain and specialized needs. In this paper, we examine the entire continuum of agent based toolkits. We characterize each based on 5 important characteristics users consider when choosing a toolkit, and then we categorize the characteristics into user-friendly taxonomies that aid in rapid indexing and easy reference.Agent Based Modeling, Individual Based Model, Multi Agent Systems

Improved Bayesian multimodeling: Integration of copulas and Bayesian model averaging

Bayesian Model Averaging (BMA) is a popular approach to combine hydrologic forecasts from individual models, and characterize the uncertainty induced by model structure. In the original form of BMA, the conditional probability density function (PDF) of each model is assumed to be a particular probability distribution (e.g. Gaussian, gamma, etc.). If the predictions of any hydrologic model do not follow certain distribution, a data transformation procedure is required prior to model averaging. Moreover, it is strongly recommended to apply BMA on unbiased forecasts, whereas it is sometimes difficult to effectively remove bias from the predictions of complex hydrologic models. To overcome these limitations, we develop an approach to integrate a group of multivariate functions, the so-called copula functions, into BMA. Here, we introduce a copula-embedded BMA (Cop-BMA) method that relaxes any assumption on the shape of conditional PDFs. Copula functions have a flexible structure and do not restrict the shape of posterior distributions. Furthermore, copulas are effective tools in removing bias from hydrologic forecasts. To compare the performance of BMA with Cop-BMA, they are applied to hydrologic forecasts from different rainfall-runoff and land-surface models. We consider the streamflow observation and simulations for ten river basins provided by the Model Parameter Estimation Experiment (MOPEX) project. Results demonstrate that the predictive distributions are more accurate and reliable, less biased, and more confident with small uncertainty after Cop-BMA application. It is also shown that the post-processed forecasts have better correlation with observation after Cop-BMA application

A Mulimodeling Framework for Complex Learning Activity Designs

This paper proposes a modeling framework for learning activities centered on the design of their components (pedagogical instruments). The learning activity is represented as learning object where the structural components are the reusable objects representing the pedagogical instruments. This purpose presents a new current of learning activity design based on activity theory where its design means the specification of its specific teaching materials called pedagogical instruments, this material has the mediation role between the learner and the objects presented in the activity. The outcome of the presented project should be the convergence of cognitive, didactic, interface and content designs

DESIGNING LEARNING ACTIVITY TO BE INDIVIDUALIZED

Abstract: The modelling of the learning individualization process is a complex problem which needs multidisciplinary knowledge. The variety of decision problems and of complex domain will never be just one method of model-based decision support. For that making rational decision should be distributed in different levels using various types of knowledge and models. The multi-modelling of the learning activity imply specifying for models of each activity: The didactic model, the knowledge object model, the interface model and the cognitive model given by the actors of design. We propose in this paper a new current of learning activity design based on activity theory where the design of the learning activity means the specification of its specific teaching materials called pedagogical instruments, this material has the mediation role between the leaner and the objects presented in the activity

Stability Analysis of Microgrid Islanding Transients based on Interconnected Dissipative Subsystems

To ensure successful islanding of microgrids after a fault has occurred, the transient stability should be analyzed under a set of expected operating conditions during the design and operation of microgrids. Transient stability analysis is conventionally performed with time-domain analysis which is computationally expensive and does not quantify the stability margin. Energy-based methodologies can determine the stability margin, however existing methodologies require significant simplifications to be applied to the microgrid model. The energy-based stability analysis methodology proposed in this paper enables the analysis of high-dimension nonlinear microgrid systems and quantification of the stability margin within reasonable time. The performance of the methodology is validated by analyzing a case study microgrid and comparing the results to time-domain analysis and to a state-of-the-art methodology proposed in the literature. The results indicate that the proposed methodology has a significantly lower computational burden and similar accuracy compared to existing energy-based methodologies. The methodology is able to improve the probability of stable islanding of the case study microgrid from 74% up to 94% when only optimizing the design, and up to 100% when optimizing design and control actions

Proposition d'une approche de modélisation et de diagnostic du comportement des barrages

National audienceCet article présente le développement d'une méthode de diagnostic basée sur une approche multi-modèles pour le diagnostic du comportement des barrages. Trois modèles sont décrits : un modèle structurel, un modèle comportemental et un modèle fonctionnel. Le contexte particulier des barrages et notamment le fait que les modèles numériques sont peu nombreux nous a amenés à proposer un modèle structurel et un modèle comportemental originaux. La définition d'un modèle structurel unique pour l'ensemble des composants reposant sur un faible nombre de variables permet de concilier efficacité calculatoire et efficacité du diagnostic. Le diagnostic restitue plusieurs éléments : les composants, process et phénomènes impliqués mais également une identification des causes et une analyse des mécanismes au cours du temps. / This article presents the development of a diagnostic method for dam behaviour. This method is based on multimodelling reasoning. Three models are described: a structural model, a behavioural model and a functional model. The scarcity of numerical models leads us to propose original structural and behavioural models. A single structural model relying on few variables is defined for all the components. It allows a computing efficiency along with a reliable diagnosis. The diagnosis produces several elements: the components, processes and phenomena involved in the faulty behaviour, an identification of the causes of the faulty behaviour and an analysis of mechanisms through time