Finite Memory Observers for linear time-varying systems: Theory and diagnosis applications

Fault detection and diagnosis are important issues in process engineering. Hence, a considerable interest exists in this field now from industrial practitioners as well as academic researchers, as opposed to 30 years ago. The literature on process fault diagnosis, ranging from analytical methods to artificial intelligence and statistical approaches, is largely widespread. In this paper, the modeling of the real process is known, and the state-space representation is used. The properties of the Finite Memory Observer (FMO) are studied from a global point of view for the class of linear time-varying (LTV) systems with stochastic noises. The FMO performances are framed by the study of their properties, and that of their influences on diagnosis results. Fundamentally, the generation of residuals is an essential procedure in diagnosis. So, the determination of the optimal window length of the observer is resolved, and the generation of residuals for diagnosis completed. In the first part, the design of the observer and the residual generation are shown. The second part is devoted to the study of the sensitivity and robustness of the observer and of residuals generated from the observer.     

Defining Excellence

The following excerpts are from Chapter Two of Mario D. Fantini's 1986 Regaining Excellence in Education, reprinted by permission of Merrill Publishing Company.     

Encountering Productive Forms of Complexity in Learning Modern Physics

This paper aims at supporting the claim that some forms of hyper-simplification, by making physics seem easy, are at risk of dangerously distorting the content as well as the process of learning physics. The paper presents examples of dangerous simplifications in the teaching of quantum physics. Then, examples of productive forms of complexity are discussed, both as criteria for designing teaching proposals, and for realizing appropriate learning environments, namely properly complex territories. Empirical results, from a teaching/learning experiment on quantum physics at upper secondary school (grade 13), are reported. These results show examples of students’ reactions to travelling through a complex territory, and allow us to argue that unavoidable difficulty in learning quantum physics can be transformed into cultural challenges within reach of secondary school students.     

Defining and Operationalizing Appropriation for Science Learning

The goal of this article is to contribute to understanding the interplay between students' disciplinary engagement and their identity construction. The term appropriation, borrowed from scholars in linguistics and education, was chosen to capture this broader sense of productive learning that sits at the nexus of disciplinary engagement and identity. Appropriation implies deep conceptual understanding, but it also involves a reflexive process of transforming scientific discourse in a way that is authentic and personal. The core aim of this article is to turn the term appropriation into a theoretical construct by means of an analytic process of defining, operationalizing, and testing the definition against student interview and classroom data. Five discourse markers for operationalizing appropriation were discovered through this process. Appropriation, in our study, implies students’ discourse is (A) an expression of a personal “signature“ idea, (B) grounded in the discipline, (C) thick, in that it involves a metacognitive and epistemological dimension, (D) non-incidental, in the sense of being consistently used throughout classroom activities, and (E) a carrier of social relationships, in that it positions the student within classroom. The study is grounded in an extended intervention on thermodynamics in an Italian secondary school class (grade 12).     

Patterns for reform in American teacher education

Public accountability in America has led to the reform of teacher preparation. A competency-based fieldcentered approach is emerging. The two major processes for achieving reform are the development of alternative teacher education institutions and the conversion of existing ones. The political and educational aspects of each process are considered.

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Résumé La réforme de la formation des maîtres aux Etats-Unis a été amenée par le développement de l'idee de responsabilité publique. On remarque l'élaboration d'une approche fondée sur la compétence pratique. Les deux principaux facteurs de cette réforme sont le développement d'un nouveau genre d'établissements pour la formation des maîtres et la transformation de ceux qui existent actuellement. Cet article fait l'exposé des aspects politique et éducationnel de chacun de ces facteurs.

     

Finite Memory Observers for linear time-varying systems. Part II: Observer and residual sensitivity

Fault detection and diagnosis are important issues in process engineering. Hence, considerable interest is growing in this field from industrial practitioners as well as academic researchers, as opposed to 30 years ago. This paper focusses on a model-based approach for fault detection. This approach is based on Finite Memory Observers (FMO), properties of this observer are presented in the first part of our work (Graton et al., 2014 [1]), the main results of this paper are recalled at the beginning of this paper and constitute the basis of this second part. Properties of the Finite Memory Observer (FMO) are studied from a global point of view for the class of linear time-varying (LTV) systems with stochastic noises. FMO performances take their framework from the study of their properties, and from the study of their influences on diagnosis results. Fundamentally, the generation of residuals is essential in a diagnosis procedure. In Graton et al. (2014) [1], the design for the finite memory observer is shown, the determination of its optimal window length is solved, and the generation of residuals for diagnosis is completed. This paper is the second part of this work and is devoted to the study of the observer and residual sensitivity towards model parameter variations and noises.