Plenary speak: 1: Nonlinear Fault Diagnosis of Dynamical Systems: An Intelligent Control Framework

Abstract

One of the key goals of intelligent control systems is to achieve high performance with increased reliability, availability, and automation of maintenance procedures. Moreover, the continuous demand for greater productivity has led to more challenging operating conditions for many modern industrial systems. Such conditions increase the possibility of system faults, which are characterized by critical and unpredictable changes in system dynamics. The goal of this presentation is to provide a unified methodology for detecting, isolating and accommodating both abrupt and incipient faults in a class of nonlinear dynamic systems. A detection and approximation estimator is used for online health monitoring. Once a fault is detected, a bank of isolation estimators is activated for the purpose of fault isolation. A key design issue is the adaptive residual threshold associated with each isolation estimator. On the basis of the fault information obtained by the fault-diagnosis procedure, a fault-tolerant control component is designed to compensate for the effects of faults. Various adaptive approximation techniques and learning algorithms will be presented and illustrated, and directions for future research will be discussed.The technical and social systems of the present day are ever more complex and complicated objects. Their models are characterized by large numbers of state and control variables, time delays, and different time constants. Also they show constraints in their information infrastructure and risk sensitivity aspects. Such systems are called large–scale complex systems (LSS). Hierarchical approach has been for several decades one of the most utilized methodologies for controlling large–scale systems. When human intervention is necessary decision support systems (DSS) can represent a solution. A DSS is an adaptive and evolving information system meant to implement several of the functions of a support team that would otherwise be needed to help the decision-maker to overcome his/her limits and constraints he/she may face when approaching decision problems that count in the organisation. This paper aims at reviewing several aspects concerning LSS control and the utilization and technology of DSS. Particular emphasis is put on real-time DSS and multiparticipant (group) DSS. Several advanced solutions such as mixed knowledge systems, that combine numerical methods with AI-based tools, and the prospects of using Ambient Intelligence concepts in DSS construction are described.