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Nonlinear Modeling
Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis. It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.
Control of Solar Energy Systems
Control of Solar Energy Systems details the main solar energy systems, problems involved with their control, and how control systems can help in increasing their efficiency. Thermal energy systems are explored in depth, as are photovoltaic generation and other solar energy applications such as solar furnaces and solar refrigeration systems. This second and updated edition of Advanced Control of Solar Plants includes new material on: solar towers and solar tracking; heliostat calibration, characterization and offset correction; solar radiation, estimation, prediction, and computation; and integrated control of solar plants. This new edition contains worked examples in the text as well as proposed exercises and simulation models and so will be of great use to the student and academic, as well as the industrial practitioner.
Process Modelling for Control
Process Modelling for Control concentrates on the modelling steps underlying a successful control design, answering questions like: How should I carry out the identification of my process to obtain a good model? How can I assess the quality of a model before to using it in control design? How can I ensure that a controller will stabilise a real process well enough before implementation? What is the most efficient method of order reduction to simplify the implementation of high-order controllers? System identification, model/controller validation and order reduction are studied in a common framework. Detailed worked examples, representative of various industrial applications, are given. This monograph uses mathematics convenient to researchers interested in real applications and to practising engineers interested in control theory. It enables control engineers to improve their methods and provides academics and graduate students with an all-round view of recent results in modelling for control.
Tandem Cold Metal Rolling Mill Control
This book deals with a novel and practical advanced method for control of tandem cold metal rolling processes based on the emerging state-dependent Riccati equation technique. After a short history of tandem cold rolling, various types of cold rolling processes are described. A basic mathematical model of the process is discussed, and the diverse conventional control methods are compared. A detailed treatment of the theoretical and practical aspects of the state-dependent algebraic Riccati equation technique is given, with specific details of the new procedure described and results of simulations performed to verify the control model and overall system performance with the new controller coupled to the process model included. These results and data derived from actual operating mills are compared showing the improvements in performance using the new method. Material is included which shows how the new technique can be extended to the control of a broad range of large-scale complex nonlinear processes.
Computational Intelligence in Time Series Forecasting
Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.
Adaptive Voltage Control in Power Systems
Adaptive Voltage Control in Power Systems, a self-contained blend of theory and novel application, offers in-depth treatment of such adaptive control schemes. Coverage moves from power-system-modelling problems through illustrations of the main adaptive control systems, including self-tuning, model-reference and nonlinearities compensation to a detailed description of design methods: Kalman filtering, parameter-identification algorithms and discrete-time controller design are all represented. Case studies address applications issues in the implementation of adaptive voltage control.
Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003
The refereed proceedings of the Joint International Conference on Artificial Neural Networks and International Conference on Neural Information Processing, ICANN/ICONIP 2003, held in Istanbul, Turkey, in June 2003. The 138 revised full papers were carefully reviewed and selected from 346 submissions. The papers are organized in topical sections on learning algorithms, support vector machine and kernel methods, statistical data analysis, pattern recognition, vision, speech recognition, robotics and control, signal processing, time-series prediction, intelligent systems, neural network hardware, cognitive science, computational neuroscience, context aware systems, complex-valued neural networks, emotion recognition, and applications in bioinformatics.
ADEX Optimized Adaptive Controllers and Systems
This book is a simple and didactic account of the developments and practical applications of predictive, adaptive predictive, and optimized adaptive control from a perspective of stability, including the latest methodology of adaptive predictive expert (ADEX) control. ADEX Optimized Adaptive Control Systems is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. The text begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guaranty the desired control performance. The second and third par...
