Problèmes de benchmark pour l'identiifcation de modèles à temps continu: conception, résultats et perspectives

International audienceThe problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modeling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development.Ce papier traite de benchmarking de l'identification de modèles à temps continu qui sont très utilisés dans l'ingiénerie

Problèmes de benchmark pour l'identiifcation de modèles à temps continu: conception, résultats et perspectives

International audienceThe problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modeling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development.Ce papier traite de benchmarking de l'identification de modèles à temps continu qui sont très utilisés dans l'ingiénerie

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Evaluation of a Collaborative Model Using A Case Study Analysis of Watershed Planning in the Intermountain West

Planning methods that involve collaboration are gaining popularity and currently being applied in a variety of resource management issues . Based on current planning theory, researchers have proposed a conceptual collaborative model for environmental planning and management . This thesis evaluates the usefulness of the model to describe the range of factors important for the establishment and operation of collaboration in environmental planning. This iterative model suggests that collaboration emerges from a series of antecedents and then proceeds sequentially through problem setting, direction setting, implementation, and monitoring and evaluation phases. The evaluation was based on three case studies of watershed-based planning efforts in the lntermountain West. Watershed planning efforts were selected because watersheds have been identified as a suitable framework for addressing many environmental issues . In addition, watersheds frequently cross many political boundaries and therefore planning efforts in a watershed context often require collaboration between the various entities. Based on the case study analysis, the model seems to realistically describe fundamental collaborative elements in environmental planning . Factors that proved to be particularly important include the involvement of stakeholders in data collection and analysis and the establishment of measurable objectives . Informal face to face dialogue and watershed field tours were critical for identifying issues and establishing trust among stakeholders. Group organizational structure also plays a key role in facilitating collaboration . From this analysis, suggestions for refining the model are proposed. In addition , key elements that planners should consider when embarking on a collaborative effort are highlighted

Leveraging Epidemiology to Improve Risk Assessment.

The field of environmental public health is at an important crossroad. Our current biomonitoring efforts document widespread exposure to a host of chemicals for which toxicity information is lacking. At the same time, advances in the fields of genomics, proteomics, metabolomics, genetics and epigenetics are yielding volumes of data at a rapid pace. Our ability to detect chemicals in biological and environmental media has far outpaced our ability to interpret their health relevance, and as a result, the environmental risk paradigm, in its current state, is antiquated and ill-equipped to make the best use of these new data. In light of new scientific developments and the pressing need to characterize the public health burdens of chemicals, it is imperative to reinvigorate the use of environmental epidemiology in chemical risk assessment. Two case studies of chemical assessments from the Environmental Protection Agency Integrated Risk Information System database are presented to illustrate opportunities where epidemiologic data could have been used in place of experimental animal data in dose-response assessment, or where different approaches, techniques, or studies could have been employed to better utilize existing epidemiologic evidence. Based on the case studies and what can be learned from recent scientific advances and improved approaches to utilizing human data for dose-response estimation, recommendations are provided for the disciplines of epidemiology and risk assessment for enhancing the role of epidemiologic data in hazard identification and dose-response assessment

Integrating Values, Purposes, and Visions for Responsible Development

This chapter highlights a study showing that knowledge sharing and envisioning processes can have positive effects on human and social capital growth within a network. The chapter begins by arguing that a responsible development perspective can be more proactive approach than a sustainability perspective. Some actors (non-profit, public, and private) have achieved responsible development goals by integrating values, purposes and visions. More specifically, we conducted a study testing a methodology that can guide a process of building a strategic vision within a network with the goal of improving their responsible development orientation. The chosen methodology is “Participatory Action Research”. The implementation of the envisioning process was studied via quantitative/qualitative research tools. The methodology was tested in an official cross-country project funded by the European Commission. The project was selected as a best practice by the same European Union Commission. The study highlights the importance of envisioning processes in building social and human capital at the inter-organizational level and, in particular, in highly complex sectors such as those oriented towards improving social responsibility. In fact, work on the envisioning process itself represents an essential instrument for developing strategic objectives to be shared among actors within networks that intend to promote responsible development and improve their human and social capital. This bottom-up process of envisioning can also facilitate cultural interaction among community members, even in a cross-country context. This relevant “learning-by-interacting” experience, can create a growth process for the human and social capital of entire communities. The creation of social capital also promotes the development of shared knowledge and advances leading to the general understanding of common core objectives and appropriate ways of acting within the social system. The chapter ends with recommendations for future research