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The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.
The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. Design methods for diagnostic systems and fault-tolerant controllers are presented for processes that are described by analytical models, by discrete-event models or that can be dealt with as quantised systems. Four case studies on pilot processes show the applicability of the presented methods. The theoretical results are illustrated by two running examples which are used throughout the book. The book addresses engineering students, engineers in industry and researchers who wish to get a survey over the variety of approaches to process diagnosis and fault-tolerant control.
Sets out core theory and reviews new methods and applications to show how hybrid systems can be modelled and understood.
Event-based control is a means to reduce the information exchange over the feedback link in networked control systems in order to avoid an overload of the digital network which generally degrades the performance of the overall control loop. This thesis presents a novel state-feedback approach to event-based control which allows approximating a continuous-time state-feedback loop with arbitrary precision while adapting the communication over the feedback link to the effect of unknown disturbances. The focus of this thesis lies in complementing the event-based state-feedback control by deriving new properties, proposing alternative methods for the analysis and improving the components of the closed-loop system. Moreover, suitable strategies are proposed to deal with imprecise information about the plant and imperfect communication links. The theoretical results are evaluated by simulations and experiments using a thermofluid process.
This work considers the problem of identifying the fault in a faulty dynamical system on the basis of the system's input and output signals only. For this purpose, a model-based method for the design of diagnostic tests which consist of specific input signals and appropriate residual generators is developed. The method extends the structure graph of dynamical systems in order to represent the couplings in a system which has been brought to a specific operating region. The resulting local structure graph is used to determine specific residual generators which can distinguish between faults on the basis of the system's input and output signals in the corresponding operating region. Algorithms to determine advantageous operating regions and input signals which drive the system into such operating regions are given. The application of the method to determine diagnostic tests is demonstrated using a typical automotive system, a throttle valve.
The safe and reliable operation of technical systems is of great significance for the protection of human life and health, the environment, and of the vested economic value. The correct functioning of those systems has a profound impact also on production cost and product quality. The early detection of faults is critical in avoiding performance degradation and damage to the machinery or human life. Accurate diagnosis then helps to make the right decisions on emergency actions and repairs. Fault detection and diagnosis (FDD) has developed into a major area of research, at the intersection of systems and control engineering, artificial intelligence, applied mathematics and statistics, and suc...
This book presents novel methods of fault-tolerant control theory in a discrete-event system framework. Nondeterministic input/output automata are used to model nominal and faulty technological systems. The main contributions are the following: Control design method for discrete-event systems Fault modeling technique for actuator, sensor and system internal faults and failures Off-line and on-line control reconfiguration based on trajectory re-planning and input/output adaptation. Two small size running examples are used to explain the developed methods. Experiments on a manufacturing cell demonstrate the application of these methods in a realistic environment. The state of the art is provided on methods for modeling, supervisory control and fault-tolerant control of discrete-event systems.
The problem of jointly designing a robust controller and an intelligent scheduler for networked control systems (NCSs) is addressed in this thesis. NCSs composing of multiple plants that share a single channel communication network with uncertain time-varying transmission times are modeled as switched polytopic systems with additive norm-bounded uncertainty. Switching is deployed to represent scheduling, the polytopic uncertainty to overapproximatively describe the uncertain time-varying transmission times. Based on the resulting NCS model and a state feedback control law, the control and scheduling codesign problem is then introduced and formulated as a robust (minimax) optimization problem...