Motion Control of Functionally Related Systems


Book Description

This book is concerned with the development of design techniques for controlling motion of mechanical systems which are employed to execute certain tasks acting collaboratively. The book introduces unified control design procedure for functionally related systems. The controllers for many different tasks in motion control can be successfully designed by applying the proposed simple procedure. The book gives an overview of the control methods appearing in the motion control area and the detailed design procedures for the class of systems that are required to execute certain task together. Tasks can generally be divided in their components, denoted as functions in the book. It is shown how dynamics of those tasks can be described. Based on the presented description, several control methods were discussed. Applicability of the introduced control design approach was demonstrated in subsequent chapters for various tasks.




Motion Control Systems


Book Description

Motion Control Systems is concerned with design methods that support the never-ending requirements for faster and more accurate control of mechanical motion. The book presents material that is fundamental, yet at the same time discusses the solution of complex problems in motion control systems. Methods presented in the book are based on the authors' original research results. Mathematical complexities are kept to a required minimum so that practicing engineers as well as students with a limited background in control may use the book. It is unique in presenting know-how accumulated through work on very diverse problems into a comprehensive unified approach suitable for application in high demanding, high-tech products. Major issues covered include motion control ranging from simple trajectory tracking and force control, to topics related to haptics, bilateral control with and without delay in measurement and control channels, as well as control of nonredundant and redundant multibody systems. Provides a consistent unified theoretical framework for motion control design Offers graduated increase in complexity and reinforcement throughout the book Gives detailed explanation of underlying similarities and specifics in motion control Unified treatment of single degree-of-freedom and multibody systems Explains the fundamentals through implementation examples Based on classroom-tested materials and the authors' original research work Written by the leading researchers in sliding mode control (SMC) and disturbance observer (DOB) Accompanying lecture notes for instructors Simulink and MATLAB® codes available for readers to download Motion Control Systemsis an ideal textbook for a course on motion control or as a reference for post-graduates and researchers in robotics and mechatronics. Researchers and practicing engineers will also find the techniques helpful in designing mechanical motion systems.




Control of Nonlinear Systems


Book Description

The book Control of Nonlinear Systems–Stability and Performance fills a crucial gap in the field of nonlinear control systems by providing a comprehensive yet accessible treatment of the subject. Unlike many existing texts that are either too complex for beginners or omit essential topics, this book strikes the right balance of mathematical rigor and practicality. The main objective of the book is to simplify and unify the existing techniques for designing and analyzing control systems for nonlinear systems. It aims to alleviate confusion and difficulty in understanding these methods, making it an invaluable resource for students, researchers, and practitioners in the field. By presenting the material in a tutorial manner, the book enhances the reader's understanding of the design and analysis of a wide range of control methods for nonlinear systems. The emphasis on stability and performance highlights the practical relevance of the concepts discussed in the book. Overall, Control of Nonlinear Systems–Stability and Performance is a valuable contribution to the field of nonlinear control systems. Its emphasis on practical applications and its accessible presentation make it an indispensable resource for engineers seeking to enhance their knowledge and skills in this important area of control theory.




Distributed Adaptive Consensus Control of Uncertain Multi-Agent Systems


Book Description

Multi-agent systems are special networked systems full of research interest and practical sense, which are abundant in real life, ranging from mobile robot networks, intelligent transportation management, to multiple spacecraft, surveillance and monitoring. Consensus control is one of the most typical and hot research issues for multi-agent systems. Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems provides innovative technologies to design and analyze distributed adaptive consensus for multi-agent systems with model uncertainties. Based on the basic graph theory and adaptive backstepping control, this monograph: · Describes the state of the art on distributed adaptive control, finite-time consensus control and event-triggered consensus control · Studies distributed adaptive consensus under directed communication graph condition: the methods with linearly parametric reference, hierarchical decomposition, and design of auxiliary filers · Explores adaptive finite-time consensus for uncertain nonlinear systems · Considers distributed adaptive consensus with event-triggered communication via state feedback and output feedback · Investigates distributed adaptive formation control of nonholonomic mobile robots with experimental verification · Provides distributed adaptive attitude synchronization control schemes for multiple spacecraft with event-triggered communication Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems can help engineering students and professionals to efficiently learn distributed adaptive control design tool for handling uncertain multi-agent systems with directed communication graph, guaranteeing finite-time convergence and saving communication resources.




Adaptive Control of Dynamic Systems with Uncertainty and Quantization


Book Description

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.




Nonlinear Pinning Control of Complex Dynamical Networks


Book Description

This book presents two nonlinear control strategies for complex dynamical networks. First, sliding-mode control is used, and then the inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6 are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning. The book is organized in four sections. The first one covers mathematical preliminaries, with a brief review for complex networks, and the pinning methodology. Additionally, sliding-mode control and inverse optimal control are introduced. Neural network structures are also discussed along with a description of the high-order ones. The second section presents the analysis and simulation results for sliding-mode control for identical as well as non-identical nodes. The third section describes analysis and simulation results for inverse optimal control considering identical or non-identical nodes. Finally, the last section presents applications of these schemes, using gene regulatory networks and microgrids as examples.




Maneuverable Formation Control in Constrained Space


Book Description

Inspired by the community behaviors of animals and humans, cooperative control has been intensively studied by numerous researchers in recent years. Cooperative control aims to build a network system collectively driven by a global objective function in a distributed or centralized communication network and shows great application potential in a wide domain. From the perspective of cybernetics in network system cooperation, one of the main tasks is to design the formation control scheme for multiple intelligent unmanned systems, facilitating the achievements of hazardous missions – e.g., deep space exploration, cooperative military operation, and collaborative transportation. Various challenges in such real-world applications are driving the proposal of advanced formation control design, which is to be addressed to bring academic achievements into real industrial scenarios. This book extends the performance of formation control beyond classical dynamic or stationary geometric configurations, focusing on formation maneuverability that enables cooperative systems to keep suitable spacial configurations during agile maneuvers. This book embarks on an adventurous journey of maneuverable formation control in constrained space with limited resources, to accomplish the exploration of an unknown environment. The investigation of the real-world challenges, including model uncertainties, measurement inaccuracy, input saturation, output constraints, and spatial collision avoidance, brings the value of this book into the practical industry, rather than being limited to academics.




Variable Gain Control and Its Applications in Energy Conversion


Book Description

The variable gain control method is a new construction technique for the control of nonlinear systems. By properly conducting state transformation that depends on the variable gains, the control design problem of nonlinear systems can be transformed into a gain construction problem, thus effectively avoiding the tedious iterative design procedure. Different from the classical backstepping method and forwarding design method, the structure of variable gain control is simpler in the sense that fewer design parameters are required, facilitating the improvement of system control performance. To highlight the learning, research, and promotion of variable gain control, Variable Gain Control and Its Applications in Energy Conversion is written based on the research results of peers at home and abroad and combining our latest research. This book presents innovative technologies for designing variable gain controllers for nonlinear systems. It systematically describes the origin and principles of variable gain control for nonlinear systems, focuses on the controller design and stability analysis, and reflects the latest research. In addition, variable gain control methods applied to energy conversion are also included. Discussion remarks are provided in each chapter highlighting new approaches and contributions to emphasize the novelty of the presented design and analysis methods. In addition, simulation results are given in each chapter to show the effectiveness of these methods. It can be used as a reference book or a textbook for students with some background in feedback control systems. Researchers, graduate students, and engineers in the fields of control, information, renewable energy generation, electrical engineering, mechanical engineering, applied mathematics, and others will benefit from this book.




Optimal Event-Triggered Control Using Adaptive Dynamic Programming


Book Description

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 for each case. The book begins by providing background on linear and nonlinear systems, NCS, networked imperfections, distributed systems, adaptive dynamic programming and optimal control, stability theory, and optimal adaptive event-triggered controller design in continuous-time and discrete-time for linear, nonlinear and distributed systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for infinite horizons. The text then: Introduces event triggered control of linear and nonlinear systems, describing the design of adaptive controllers for them Presents neural network-based optimal adaptive control and game theoretic formulation of linear and nonlinear systems enclosed by a communication network Addresses the stochastic optimal control of linear and nonlinear NCS by using neuro dynamic programming Explores optimal adaptive design for nonlinear two-player zero-sum games under communication constraints to solve optimal policy and event trigger condition Treats an event-sampled distributed linear and nonlinear systems to minimize transmission of state and control signals within the feedback loop via the communication network Covers several examples along the way and provides applications of event triggered control of robot manipulators, UAV and distributed joint optimal network scheduling and control design for wireless NCS/CPS in order to realize industry 4.0 vision An ideal textbook for senior undergraduate students, graduate students, university researchers, and practicing engineers, Optimal Event Triggered Control Design using Adaptive Dynamic Programming instills a solid understanding of neural network-based optimal controllers under event-sampling and how to build them so as to attain CPS or Industry 4.0 vision.




Intelligent Fault Diagnosis and Accommodation Control


Book Description

Control systems include many components, such as transducers, sensors, actuators and mechanical parts. These components are required to be operated under some specific conditions. However, due to prolonged operations or harsh operating environment, the properties of these devices may degrade to an unacceptable level, causing more regular fault occurrences. It is therefore necessary to diagnose faults and provide the fault-accommodation control which compensates for the fault of the component by substituting a configuration of redundant elements so that the system continues to operate satisfactorily. In this book, we present a result of several years of work in the area of fault diagnosis and fault-accommodation control. It aims at information estimate methods when faults occur. The book uses the model built from the plant or process, to detect and isolate failures, in contrast to traditional hardware or statistical technologies dealing with failures. It presents model-based learning and design technologies for fault detection, isolation and identification as well as fault-tolerant control. These models are also used to analyse the fault detectability and isolability conditions and discuss the stability of the closed-loop system. It is intended to report new technologies in the area of fault diagnosis, covering fault analysis and control strategies of design for various applications. The book addresses four main schemes: modelling of actuator or sensor faults; fault detection and isolation; fault identification, and fault reconfiguration (accommodation) control. It also covers application issues in the monitoring control of actuators, providing several interesting case studies for more application-oriented readers.