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Control of Complex Systems
In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: “Introduction and Background on Control Theory”, “Adaptive Control and Neuroscience”, “Adaptive Learning Algorithms”, “Cyber-Physical Systems and Cooperative Control”, “Applications”. The diversity of the research presented gives the reader a unique opportuni...
Optimal Event-Triggered Control Using Adaptive Dynamic Programming
Optimal Event-triggered Control using Adaptive Dynamic Programming discusses event triggered controller design which includes optimal control and event sampling design for linear and nonlinear dynamic systems including networked control systems (NCS) when the system dynamics are both known and uncertain. The NCS are a first step to realize cyber-physical systems (CPS) or industry 4.0 vision. The authors apply several powerful modern control techniques to the design of event-triggered controllers and derive event-trigger condition and demonstrate closed-loop stability. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included f...
Optimal Networked Control Systems with MATLAB
Optimal Networked Control Systems with MATLAB® discusses optimal controller design in discrete time for networked control systems (NCS). The authors apply several powerful modern control techniques in discrete time to the design of intelligent controllers for such NCS. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included for each case. The book begins by providing background on NCS, networked imperfections, dynamical systems, stability theory, and stochastic optimal adaptive controllers in discrete time for linear and nonlinear systems. It lays the foundation for reinforcement learning-based optimal adaptive controller u...
Event-Triggered Transmission Protocol in Robust Control Systems
Controlling uncertain networked control system (NCS) with limited communication among subcomponents is a challenging task and event-based sampling helps resolve the issue. This book considers event-triggered scheme as a transmission protocol to negotiate information exchange in resilient control for NCS via a robust control algorithm to regulate the closed loop behavior of NCS in the presence of mismatched uncertainty with limited feedback information. It includes robust control algorithm for linear and nonlinear systems with verification. Features: Describes optimal control based robust control law for event-triggered systems. States results in terms of Theorems and Lemmas supported with detailed proofs. Presents the combination of network interconnected systems and robust control strategy. Includes algorithmic steps for precise understanding of the control technique. Covers detailed problem statement and proposed solutions along with numerical examples. This book aims at Senior undergraduate, Graduate students, and Researchers in Control Engineering, Robotics and Signal Processing.
Neural Network Control of Nonlinear Discrete-Time Systems
Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive ca...
Wireless Ad hoc and Sensor Networks
With modern communication networks continuing to grow in traffic, size, complexity, and variety, control systems are critical to ensure quality and effectively manage network traffic. Providing a thorough and authoritative introduction, Wireless Ad hoc and Sensor Networks: Protocols, Performance, and Control examines the theory, architectures, and technologies needed to implement quality of service (QoS) in a wide variety of communication networks. Based on years of research and practical experience, this book examines the technical concepts underlying the design, implementation, research, and invention of both wired and wireless networks. The author builds a strong understanding of general ...
Informatics in Control, Automation and Robotics 12th International Conference, ICINCO 2015 Colmar, France, July 21-23, 2015 Revised Selected Papers
The present book includes a set of selected extended papers from the 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2015), held in Colmar, France, from 21 to 23 July 2015. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2015 re...
Reinforcement Learning
This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems. A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive research on data-driven robust control for nonlinear systems with unknown dynamics and multi-player systems follows. Data-driven optim...
