Model-based Process Supervision
A Bond Graph Approach
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Beschreibung
Model-based fault detection and isolation requires a mathematical model of the system behaviour. Modelling is important and can be difficult because of the complexity of the monitored system and its control architecture. The authors use bond-graph modelling, a unified multi-energy domain modelling method, to build dynamic models of process engineering systems by composing hierarchically arranged sub-models of various commonly encountered process engineering devices. The structural and causal properties of bond-graph models are exploited for supervisory systems design.
The structural properties of a system, necessary for process control, are elegantly derived from bond-graph models by following the simple algorithms presented here. Additionally, structural analysis of the model, augmented with available instrumentation, indicates directly whether it is possible to detect and/or isolate faults in some specific sub-space of the process. Such analysis aids in the design and resource optimization of new supervision platforms.
Static and dynamic constraints, which link the time evolution of the known variables under normal operation, are evaluated in real time to determine faults in the system. Various decision or post-processing steps integral to the supervisory environment are discussed in this monograph; they are required to extract meaningful data from process state knowledge because of unavoidable process uncertainties. Process state knowledge has been further used to take active and passive fault accommodation measures.
Several applications to academic and small-scale-industrial processes are interwoven throughout. Finally, an application concerning development of a supervision platform for an industrial plant is presented with experimental validation.
Model-based Process Supervision provides control engineers and workers in industrial and academic research establishments interested in process engineering with a means to build up a practical and functional supervisory control environment and to use sophisticated models to get the best use out of their process data.
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. All evolving engineering disciplines first create a body of fundamental knowledge and then move on to new problem areas. Control engineering has now reached this level of maturity and is tackling new theoretical and applications areas. The field of nonlinear systems is receiving much research attention as are the problems of industrial supervisory control. The twin drivers of research into supervisory control are the use of new technology (computer networks and distributed sensor networks, for example) and the search for theoretical techniques to describe and solve supervisory control application problems.
Use of bond graphs to model industrial processes for supervision speeds up validation of design control design aspects like sensor/actuator placement Automatic generation of algorithms to monitor processes in healthy and faulty operation Genuine integrated design uses a common modelling tool for process simulation, control analysis and fault detection and isolation Includes supplementary material: sn.pub/extras
Autor*in
Arun Kumar Samantaray
Themen in »Model-based Process Supervision«
Bond Graphs Composing Control Control Applications Control Engineering FDI Fault Detection Modelling Normal Process Control Process Engineering Sensor Simulation Supervisory Control optimization
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From the reviews:
“This book is written for students and researchers interested in bond graph model-based control and supervision. The book presents a detailed up-to-date view of how bond graph modeling can be applied to fault diagnosis and control of engineering processes.” (IEEE Control Systems Magazine, Vol. 30, February, 2010)
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