A CPN-Approach for DistributedAbductive Reasoning : Application to Causal Model-Based Diagnosis

This thesis deals with fault diagnosis of distributed systems from a model-based view where Coloured Petri Nets are used to describe the systembehaviour. The systems concerned here are those comprising different interactingsubsystems. Coloured Behavioural Petri Nets are defined as a particular CPNintended for the description of a system’s causal behaviour, where each transitionis labelled with a matrix describing explicitly its firing ways. The use of suchmatrices helps in tackling the problem of complexity during backward analysis,and gives rise to a very specific technique based on reachability of CBPNs calledCW-analysis. CBPNs together with the CW-analysis are used to develop a dis-tributed model-based diagnosis approach. The diagnostic system is defined as setof diagnostic agents where each is assigned to diagnose a subsystem. Accordingly,the system model consists of a set of place-bordered CBPNs, whereas CW-analysisis exploited to implement a local diagnosis scheme. Once local diagnoses are ob-tained by the different agents, a cooperation process should be initiated to ensureglobal consistency of such diagnoses

Correctness of services and their composition

We study correctness of services and their composition and investigate how the design of correct service compositions can be systematically supported. We thereby focus on the communication protocol of the service and approach these questions using formal methods and make contributions to three scenarios of SOC.Wir studieren die Korrektheit von Services und Servicekompositionen und untersuchen, wie der Entwurf von korrekten Servicekompositionen systematisch unterstützt werden kann. Wir legen dabei den Fokus auf das Kommunikationsprotokoll der Services. Mithilfe von formalen Methoden tragen wir zu drei Szenarien von SOC bei

Correctness of services and their composition

We study correctness of services and their composition and investigate how the design of correct service compositions can be systematically supported. We thereby focus on the communication protocol of the service and approach these questions using formal methods and make contributions to three scenarios of SOC.Wir studieren die Korrektheit von Services und Servicekompositionen und untersuchen, wie der Entwurf von korrekten Servicekompositionen systematisch unterstützt werden kann. Wir legen dabei den Fokus auf das Kommunikationsprotokoll der Services. Mithilfe von formalen Methoden tragen wir zu drei Szenarien von SOC bei

Measurements, Models, Systems and Design

531 s.

A diagnostic investigation and a corrective model for implementing change in response to innovation

Organizational change can be described as a series of activities oriented towards modifying behaviors and structures within the organization. These series of activities are interconnected internally and externally and are affected by human, operational and environmental factors that dynamically influence decisions and processes in the organization. There has been a significant amount of work in organizational change, using both behavioral and systemic approaches. Moreover it has been argued that research in change processes should include also the dynamic relationship between change processes and outcomes to detect how organizational change context, processes and the pace of change affect performance outcomes. Despite the amount of research, there is a need for more profound studies exploring the contexts, content, and processes involved in a change initiative. This research proposes a model to help organizations implement change initiatives with an increased likelihood of success. The Influence Model for Organizational Change – IMOC - was developed with the hope of better demonstrating the dynamics that take place in the organization by using a systems engineering view. As an exercise to verify the relationships that govern IMOC a systems dynamic simulation model was partially developed. The dynamic simulation confirmed the impact of variables such as employees’ and management participation, environment and delay in implementing policies on the level of resistance to change existing in the organization.Organizational change can be described as a series of activities oriented towards modifying behaviors and structures within the organization. These series of activities are interconnected internally and externally and are affected by human, operational and environmental factors that dynamically influence decisions and processes in the organization. There has been a significant amount of work in organizational change, using both behavioral and systemic approaches. Moreover it has been argued that research in change processes should include also the dynamic relationship between change processes and outcomes to detect how organizational change context, processes and the pace of change affect performance outcomes. Despite the amount of research, there is a need for more profound studies exploring the contexts, content, and processes involved in a change initiative. This research proposes a model to help organizations implement change initiatives with an increased likelihood of success. The Influence Model for Organizational Change – IMOC - was developed with the hope of better demonstrating the dynamics that take place in the organization by using a systems engineering view. As an exercise to verify the relationships that govern IMOC a systems dynamic simulation model was partially developed. The dynamic simulation confirmed the impact of variables such as employees’ and management participation, environment and delay in implementing policies on the level of resistance to change existing in the organization

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study