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This authoritative treatment covers theory, optimal estimation and a range of practical applications. The first book on the subject, and written by leading researchers, this clear and rigorous work presents a comprehensive theory for both the stability boundary and the stability regions of a range of nonlinear dynamical systems including continuous, discrete, complex, two-time-scale and non-hyperbolic systems, illustrated with numerical examples. The authors also propose new concepts of quasi-stability region and of relevant stability regions and their complete characterisations. Optimal schemes for estimating stability regions of general nonlinear dynamical systems are also covered, and finally the authors describe and explain how the theory is applied in applications including direct methods for power system transient stability analysis, nonlinear optimisation for finding a set of high-quality optimal solutions, stabilisation of nonlinear systems, ecosystem dynamics, and immunisation problems.

Stability. --- Dynamics. --- Nonlinear control theory.

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This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The book presents a series of application examples to confirm the efficiency of the proposed nonlinear filtering and adaptive control schemes for various electromechanical systems. These include: ·         industrial robots; ·         mobile robots and autonomous vehicles; ·         electric power generation; ·         electric motors and actuators; ·         power electronics; ·         internal combustion engines; ·         distributed-parameter systems; and ·         communication systems. Differential Flatness Approaches to Nonlinear Control and Filtering will be a useful reference for academic researchers studying advanced problems in nonlinear control and nonlinear dynamics, and for engineers working on control applications in electromechanical systems.

Engineering. --- Control. --- Mechatronics. --- Artificial Intelligence (incl. Robotics). --- Computational Intelligence. --- Artificial intelligence. --- Ingénierie --- Intelligence artificielle --- Mechanical Engineering --- Engineering & Applied Sciences --- Mechanical Engineering - General --- Nonlinear control theory. --- Computational intelligence. --- Control engineering. --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- 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 --- Nonlinear theories --- Control and Systems Theory. --- Artificial Intelligence.

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This monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced phenomena consequent on limited communication capacity. Such phenomena include communication delay, packet dropout, signal quantization or saturation, randomly occurring nonlinearities and randomly occurring uncertainties. The text is self-contained, beginning with an introduction to nonlinear stochastic systems, network-induced phenomena and filtering and control, moving through a collection of the latest research results which focuses on the three aspects of: ·        the state-of-the-art of nonlinear filtering and control; ·        recent advances in recursive filtering and sliding mode control; and ·        their potential for application in networked control systems, and concluding with some ideas for future research work. New concepts such as the randomly occurring uncertainty and the probability-constrained performance index are proposed to make the network models as realistic as possible. The power of combinations of such recent tools as the completing-the-square and sums-of-squares techniques, Hamilton‒Jacobi‒Isaacs matrix inequalities, difference linear matrix inequalities, and parameter-dependent matrix inequalities is exploited in treating the mathematical and computational challenges arising from nonlinearity and stochasticity. Nonlinear Stochastic Systems with Network-Induced Phenomena establishes a unified framework of control and filtering which will be of value to academic researchers in bringing structure to problems associated with an important class of networked system and offering new means of solving them. The significance of the new concepts, models and methods presented for practical control engineering and signal processing will also make it a valuable reference for engineers dealing with nonlinear control and filtering problems.

Engineering. --- Control. --- Probability Theory and Stochastic Processes. --- Communications Engineering, Networks. --- Systems Theory, Control. --- Systems theory. --- Distribution (Probability theory). --- Telecommunication. --- Ingénierie --- Distribution (Théorie des probabilités) --- Télécommunications --- Distribution (Probability theory. --- Mechanical Engineering --- Engineering & Applied Sciences --- Mechanical Engineering - General --- Sliding mode control. --- Stochastic systems. --- Nonlinear control theory. --- Systems, Stochastic --- System theory. --- Probabilities. --- Control engineering. --- Electrical engineering. --- Control theory --- Nonlinear theories --- Stochastic processes --- System analysis --- Automatic control --- Control and Systems Theory. --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Electric engineering --- Engineering --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Control engineering --- Control equipment --- Engineering instruments --- Automation --- Programmable controllers --- Systems, Theory of --- Systems science --- Science --- Philosophy