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Nonlinear systems. --- Observers (Control theory) --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory --- Systems, Nonlinear --- System theory

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Adaptive control systems. --- Observers (Control theory) --- Nonlinear control theory. --- Control theory --- Nonlinear theories --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Self-adaptive control systems --- Artificial intelligence --- Feedback control systems --- Self-organizing systems

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This book presents theoretical and practical findings on the state estimation, diagnosis and control of complex systems, especially in the mathematical form of descriptor systems. The research is fully motivated by real-world applications (i.e., Barcelona’s water distribution network), which require control systems capable of taking into account their specific features and the limits of operations in the presence of uncertainties stemming from modeling errors and component malfunctions. Accordingly, the book first introduces a complete set-based framework for explicitly describing the effects of uncertainties in the descriptor systems discussed. In turn, this set-based framework is used for state estimation and diagnosis. The book also presents a number of application results on economic model predictive control from actual water distribution networks and smart grids. Moreover, the book introduces a fault-tolerant control strategy based on virtual actuators and sensors for such systems in the descriptor form. .

Control engineering. --- Computational complexity. --- Energy systems. --- Control and Systems Theory. --- Complexity. --- Energy Systems. --- Complexity, Computational --- Electronic data processing --- Machine theory --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Automatic control --- Observers (Control theory) --- Mathematics. --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Observers (Control theory).

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My aim, in writing this monograph, has been to remedy this omission by presenting a comprehensive and unified theory of observers for continuous-time and discrete -time linear systems. The book is intended for post-graduate students and researchers specializing in control systems, now a core subject in a number of disciplines. Forming, as it does, a self-contained volume it should also be of service to control engineers primarily interested in applications, and to mathematicians with some exposure to control problems.

Mathematical control systems --- Feedback control systems. --- Linear systems. --- Observers (Control theory). --- Observers (Control theory) --- Systems, Linear --- Differential equations, Linear --- System theory --- Feedback mechanisms --- Feedback systems --- Automatic control --- Automation --- Discrete-time systems --- Adaptive control systems --- Feedforward control systems --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory

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Many problems in decision making, monitoring, fault detection, and control require the knowledge of state variables and time-varying parameters that are not directly measured by sensors. In such situations, observers, or estimators, can be employed that use the measured input and output signals along with a dynamic model of the system in order to estimate the unknown states or parameters. An essential requirement in designing an observer is to guarantee the convergence of the estimates to the true values or at least to a small neighborhood around the true values. However, for nonlinear, large-scale, or time-varying systems, the design and tuning of an observer is generally complicated and involves large computational costs. This book provides a range of methods and tools to design observers for nonlinear systems represented by a special type of a dynamic nonlinear model - the Takagi-Sugeno (TS) fuzzy model. The TS model is a convex combination of affine linear models, which facilitates its stability analysis and observer design by using effective algorithms based on Lyapunov functions and linear matrix inequalities. Takagi-Sugeno models are known to be universal approximators and, in addition, a broad class of nonlinear systems can be exactly represented as a TS system. Three particular structures of large-scale TS models are considered: cascaded systems, distributed systems, and systems affected by unknown disturbances. The reader will find in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems. Stability analysis of TS fuzzy systems is addressed in detail. The intended audience are graduate students and researchers both from academia and industry. For newcomers to the field, the book provides a concise introduction dynamic TS fuzzy models along with two methods to construct TS models for a given nonlinear system. For additional information, see the book website at http://www.dcsc.tudelft.nl/fuzzybook/.

Fuzzy sets --- Fuzzy systems --- Mathematics --- Engineering & Applied Sciences --- Physical Sciences & Mathematics --- Computer Science --- Algebra --- Nonlinear control theory. --- Observers (Control theory) --- Fuzzy systems. --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Systems, Fuzzy --- System analysis --- Fuzzy logic --- Control theory --- Nonlinear theories --- Artificial Intelligence.