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Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain
This book provides robust analysis and synthesis tools for Markovian jump systems in the finite-time domain with specified performances. It explores how these tools can make the systems more applicable to fields such as economic systems, ecological systems and solar thermal central receivers, by limiting system trajectories in the desired bound in a given time interval. Robust Control for Discrete-Time Markovian Jump Systems in the Finite-Time Domain focuses on multiple aspects of finite-time stability and control, including: finite-time H-infinity control; finite-time sliding mode control; finite-time multi-frequency control; finite-time model predictive control; and high-order moment finit...
Multi-model Jumping Systems: Robust Filtering and Fault Detection
This book focuses on multi-model systems, describing how to apply intelligent technologies to model complex multi-model systems by combining stochastic jumping system, neural network and fuzzy models. It focuses on robust filtering, including finite-time robust filtering, finite-frequency robust filtering and higher order moment robust filtering schemes, as well as fault detection problems for multi-model jump systems, such as observer-based robust fault detection, filtering-based robust fault detection and neural network-based robust fault detection methods. The book also demonstrates the validity and practicability of the theoretical results using simulation and practical examples, like circuit systems, robot systems and power systems. Further, it introduces readers to methods such as finite-time filtering, finite-frequency robust filtering, as well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the modeling, analysis and design of the multi-model systems presented and implement filtering and fault detection analysis for various systems, including circuit, network and mechanical systems.
New Directions on Model Predictive Control
This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics
Space Physics and Aeronomy, Ionosphere Dynamics and Applications
A comprehensive review of global ionospheric research from the polar caps to equatorial regions It's more than a century since scientists first identified the ionosphere, the layer of the Earth’s upper atmosphere that is ionized by solar and cosmic radiation. Our understanding of this dynamic part of the near-Earth space environment has greatly advanced in recent years thanks to new observational technologies, improved numerical models, and powerful computing capabilities. Ionosphere Dynamics and Applications provides a comprehensive overview of historic developments, recent advances, and future directions in ionospheric research. Volume highlights include: Behavior of the ionosphere in di...
Non-monotonic Approach to Robust H? Control of Multi-model Systems
Non-monotonic Approach to Robust H8 Control of Multi-model Systems focuses on robust analysis and synthesis problems for multi-model systems based on the non-monotonic Lyapunov Functionals (LFs) approach that enlarges the stability region and improves control performance. By fully considering the diversity of switching laws, the multi-step time difference, the multi-step prediction, and the expansion of system dimension, the non-monotonic LF can be properly constructed. The focus of this book is placed on the H8 state feedback control, H8 filtering and H8 output feedback control for multi-model systems via a non-monotonic LF approach. The book's authors provide illustrative examples to show the feasibility and efficiency of the proposed methods, along with practical examples that demonstrate the effectiveness and potential of theoretical results.
Advances in Neural Networks - ISNN 2007
Annotation The three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. The 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. The papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.
Conquer the Beautiful Boss
An official writing about the skills of an official and how to rise through the ranks; a handbook about how to use a conspiracy to succeed. Let's see how the Red Second Generation Luo Tianyun and the Nong Second Generation Ma Yingjie can leverage their strength to reach the pinnacle of power one step at a time. A car accident had taken the lives of the mayor's wife and daughter. And Ma Yingjie, the mayor's secretary, accidentally discovered one of Mayor Luo Tianyun's big secrets
Radio Science
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Long-term Trends
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