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"Feedback control systems"
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Algebraic identification and estimation methods in feedback control systems
Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.
This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology.
Key features:
* Presents a radically new approach to online parameter and state estimation.
* Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.
* Includes examples in a variety of physical applications with experimental results.
* Covers the latest developments and applications.
Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.
eBook
Co-design approaches for dependable networked control systems
This book describes co-design approaches, and establishes the links between the QoC (Quality of Control) and QoS (Quality of Service) of the network and computing resources. The methods and tools described in this book take into account, at design level, various parameters and properties that must be satisfied by systems controlled through a network. Among the important network properties examined are the QoC, the dependability of the system, and the feasibility of the real-time scheduling of tasks and messages. Correct exploitation of these approaches allows for efficient design, diagnosis, and implementation of the NCS. This book will be of great interest to researchers and advanced students in automatic control, real-time computing, and networking domains, and to engineers tasked with development of NCS, as well as those working in related network design and engineering fields.
eBook
Empirical Verification of the Control System Model of Profit Rate
This note aims to empirically verify the control system model of profit rate established by Park and Yang [4]. Specifically, it is shown that the real profit rate has gradually fallen in 8 countries over the last several decades. Then, using the parameters estimated from the real data, the simulated profit rates are obtained from the control system model, and compared with the real profit rates. As a result, this note shows that although the short-run behaviors are different, the control system model well captures the long-run decline in profit rate for all countries.
Journal Article
Control System Design Guide - Using Your Computer to Understand and Diagnose Feedback Controllers (4th Edition)
This book has helped thousands of engineers to improve machine performance. This Fourth Edition of the practical guide has been updated with cutting-edge control design scenarios, models and simulations enabling apps from battlebots to solar collectors. This useful reference enhances coverage of practical applications via the inclusion of new control system models, troubleshooting tips, and expanded coverage of complex systems requirements, such as increased speed, precision and remote capabilities, bridging the gap between the complex, math-heavy control theory taught in formal courses, and the efficient implementation required in real industry settings.
eBook
Fast Finite-Time Fuzzy Control for a Class of Nonstrict Feedback Systems with Input Quantization
In this research, a fast finite-time control scheme is proposed for nonstrict feedback systems with quantized input signals. It is known that nonstrict feedback form and input quantization are common problems caused by the complexity and performance requirements in practical systems. To deal with these difficulties, the obstacle generated by the nonstrict feedback structure is first solved by a fuzzy logic system (FLS) through the amazing characteristic of the Gaussian function. Second, a nonlinear decomposition method for the hysteretic quantizer is applied to simplify the procedures of controller design and stability analysis. Next, an adaptive controller is designed using backstepping theory, and a fast finite-time stability criterion is introduced to confirm its effectiveness and stability. Then, a given simulation example and a practical nonstrict feedback application about one-link manipulator are presented to demonstrate the effectiveness and feasibility of the proposed method. The simulation results illustrate that the proposed adaptive fuzzy controller ensures all the state variables are bounded and the tracking error converges to a small interval around zero.
Journal Article