
Adaptive Control of Dynamic Systems with Uncertainty and Quantization by Jing Zhou
This book presents a series of innovative technologies and research results on adaptive control of dynamic systems with quantization, uncertainty, and nonlinearity, including the theoretical success and practical development such as the approaches for stability analysis, the compensation of quantization, the treatment of subsystem interactions, and the improvement of system tracking and transient performance. Novel solutions by adopting backstepping design tools to a number of hotspots and challenging problems in the area of adaptive control are provided.
In the first three chapters, the general design procedures and stability analysis of backstepping controllers and the basic descriptions and properties of quantizers are introduced as preliminary knowledge for this book. In the remainder of this book, adaptive control schemes are introduced to compensate for the effects of input quantization, state quantization, both input and state/output quantization for uncertain nonlinear systems and are applied to helicopter systems and DC Microgrid. Discussion remarks are provided in each chapter highlighting new approaches and contributions to emphasize the novelty of the presented design and analysis methods. Simulation results are also given in each chapter to show the effectiveness of these methods.
This book is helpful to learn and understand the fundamental backstepping schemes for state feedback control and output feedback control. It can be used as a reference book or a textbook on adaptive quantized control for students with some background in feedback control systems. Researchers, graduate students, and engineers in the fields of control, information, and communication, electrical engineering, mechanical engineering, computer science, and others will benefit from this book.
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Chaos in Automatic Control
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Advances in Missile Guidance, Control, and Estimation
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Robust Formation Control for Multiple Unmanned Aerial Vehicles
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Analysis and Synthesis of Fuzzy Control Systems
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Control of Nonlinear Systems via PI, PD and PID
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Wireless Ad hoc and Sensor Networks
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Modeling and Control of Complex Systems
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Distributed Adaptive Consensus Control of Uncertain Multi-Agent Systems
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Optimal Event-Triggered Control Using Adaptive Dynamic Programming
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Control of Nonlinear Systems
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Maneuverable Formation Control in Constrained Space
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Reinforcement Learning and Dynamic Programming Using Function Approximators
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Quantitative Process Control Theory
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Modeling and Control for Micro/Nano Devices and Systems
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Sliding Mode Control in Electro-Mechanical Systems
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System Modeling and Control with Resource-Oriented Petri Nets
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Variable Gain Control and Its Applications in Energy Conversion
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Optimal Control
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Cooperative Control of Multi-Agent Systems
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Multi-Agent Systems
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Deterministic Learning Theory for Identification, Recognition, and Control
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Synchronization and Control of Multiagent Systems
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Anti-Disturbance Control for Systems with Multiple Disturbances
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Tensor Product Model Transformation in Polytopic Model-Based Control
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Fundamentals in Modeling and Control of Mobile Manipulators
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Intelligent Diagnosis and Prognosis of Industrial Networked Systems
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Nonlinear Control of Dynamic Networks
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End-to-End Adaptive Congestion Control in TCP/IP Networks
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Electric and Plug-in Hybrid Vehicle Networks
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Fuzzy Controller Design
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Modern Control Engineering
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Nonlinear Control of Electric Machinery
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Discrete-Time Recurrent Neural Control
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Nonlinear Pinning Control of Complex Dynamical Networks
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Classical Feedback Control with Nonlinear Multi-Loop Systems
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Optimal Networked Control Systems with MATLAB
Jing Zhou is currently a Full Professor at the Faculty of Engineering and Science, University of Agder, Norway, and a Research Director of the Priority Research Center of Mechatronics.
Lantao Xing is a Presidential Postdoctoral Fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
Changyun Wen is currently a Full Professor at the Nanyang Technological University, Singapore.
| SKU | Unavailable |
| ISBN 13 | 9781032009827 |
| ISBN 10 | 1032009829 |
| Title | Adaptive Control of Dynamic Systems with Uncertainty and Quantization |
| Author | Jing Zhou |
| Series | Automation And Control Engineering |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2024-10-08 |
| Number of pages | 233 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |







































