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• 1. Problem Statement
• 2. Internal Model Principle: Overview of Theoretical Approaches
• 3. Basic Schemes of Adaptation Algorithms
• 4. Parametric Models for Adaptive Control Design
• 5. Adaptive Tracking Reference Signals
• 6. Adaptive Rejecting External Disturbances
• 7. Adaptive Tracking in Systems with Input Delay
• 8. Adaptive Compensation in Systems with Input Delay
• 9. Internal Model Principle: Overview of Practical Applications.

This monograph is focused on control law design methods for asymptotic tracking and disturbance rejection in the presence of uncertainties. The methods are based on adaptive implementation of the Internal Model Principle (IMP). The monograph shows how this principle can be applied to the problems of asymptotic rejection/tracking of a priori uncertain exogenous signals for linear and nonlinear plants with known and unknown parameters. The book begins by introducing the problems of adaptive control, the challenges that are faced, modern methods and an overview of the IMP. It then introduces special observers for uncertain exogeneous signals affecting linear and nonlinear systems with known and unknown parameters. The basic algorithms of adaptation applied to the canonical closed-loop error models are presented. The authors then address the systematic design of adaptive systems for asymptotic rejection/tracking of a priori uncertain exosignals. The monograph also discusses the adaptive rejection/tracking of a priori uncertain exogenous signals in systems with input delay, the problems of performance improvement in disturbance rejection and reference tracking and the issue of robustness of closed-loop systems. Adaptive Regulation provides a systematic discussion of the IMP applied to a variety of control problems, making it of interest to researchers and industrial practitioners.

• Preface xi
• Series Preface xv
• Symbols and Acronyms xvii
• 1 Introduction 1
• 2 Fractional Calculus and Fractional-Order Systems 9
• 2.1 Fractional Calculus 9
• 2.1.1 Several Important Functions of Fractional Calculus 9
• 2.1.2 Fractional Integral and Derivatives 11
• 2.1.3 Some Important Lemmas 12
• 2.2 Some Typical Fractional-Order Systems 16
• 2.2.1 Fractional-Order Lorenz System 16
• 2.2.2 Fractional-Order Van Der Pol Oscillator 18
• 2.2.3 Fractional-Order Genesio-Tesi System 18
• 2.2.4 Fractional-Order Arneodo System 20
• 2.2.5 Fractional-Order Lotka-Volterra System 21
• 2.2.6 Fractional-Order Financial System 23
• 2.2.7 Fractional-Order Newton-Leipnik System 25
• 2.2.8 Fractional-Order Duffing System 27
• 2.2.9 Fractional-Order Lu System 29
• 2.2.10 Fractional-Order Three-Dimensional System 33
• 2.2.11 Fractional-Order Hyperchaotic Oscillator 35
• 2.2.12 Fractional-Order Four-Dimensional Hyperchaotic System 37
• 2.2.13 Fractional-Order Hyperchaotic Cellular Neural Network 39
• 2.3 Conclusion 41
• 3 Fractional-Order PID Controller and Fractional-Order Disturbance Observer 43
• 3.1 Problem Statement 43
• 3.2 Fractional-Order PID Controller 44
• 3.2.1 Integer-Order PID Controller 44
• 3.2.2 Fractional-Order PI?D? Controller 44
• 3.2.3 Control Based on Fractional-Order PI?D? Controller 45
• 3.3 Frequency-Domain Fractional-Order Disturbance Observer 48
• 3.3.1 Classical Integer-Order Disturbance Observer 48
• 3.3.2 Fractional-Order Disturbance Observer 49
• 3.3.3 Estimation Performance of Fractional-Order Disturbance Observer 51
• 3.3.4 Control Based on Fractional-Order Disturbance Observer 52
• 3.4 Conclusion 53
• 4 Design of Fractional-Order Controllers for Nonlinear Chaotic Systems and Some Applications 55
• 4.1 Fractional-Order Control for a Novel Chaotic SystemWithout Equilibrium 55
• 4.1.1 Problem Statement 55
• 4.1.2 Design of Chaotic System and Circuit Implementation 56
• 4.1.2.1 A Novel Chaotic System 56
• 4.1.2.2 Circuit Implementation 58
• 4.1.3 Design of Fractional-Order Controller and Stability Analysis 59
• 4.1.4 Numerical Simulation 62
• 4.1.4.1 Novel Chaotic System 62
• 4.1.4.2 Chaotic Systems with Equilibrium 63
• 4.2 Application of Chaotic System without Equilibrium in Image Encryption 68
• 4.2.1 Image Encryption Scheme 69
• 4.2.2 Histogram Analysis 69
• 4.2.3 Correlation of Two Adjacent Pixels 71
• 4.2.4 Anti-Attack Ability of Image Encryption Scheme 71
• 4.2.5 Sensitivity Analysis of Key 71
• 4.3 Synchronization Control for Fractional-Order Nonlinear Chaotic Systems 73
• 4.3.1 Problem Description 73
• 4.3.2 Design of Synchronization Controller 73
• 4.3.3 Simulation Examples 75
• 4.3.3.1 Fractional-Order Chen System 76
• 4.3.3.2 Fractional-Order Lorenz System 79
• 4.3.4 Application of Synchronization Control Scheme in Secure Communication 82
• 4.4 Conclusion 83
• 5 Sliding-Mode Control for Fractional-Order Nonlinear Systems Based on Disturbance Observer 85
• 5.1 Problem Statement 85
• 5.2 Adaptive Control Design Based on Fractional-Order Sliding-Mode Disturbance Observer 86
• 5.2.1 Design of Fractional-Order Sliding-Mode Disturbance Observer 86
• 5.2.2 Controller Design and Stability Analysis 87
• 5.3 Simulation Examples 89
• 5.3.1 Example 1 89
• 5.3.2 Example 2 91
• 5.4 Conclusion 94
• 6 Disturbance-Observer-Based Neural Control for Uncertain Fractional-Order Rotational Mechanical System 95
• 6.1 Problem Statement 95
• 6.2 Adaptive Neural Control Design 96
• 6.2.1 Design of Fractional-Order Disturbance Observer 96
• 6.2.2 Controller Design and Stability Analysis 97
• 6.3 Simulation Example 101
• 6.4 Conclusion 105
• 7 Adaptive Neural Tracking Control for Uncertain Fractional-Order Chaotic Systems Subject to Input Saturation and Disturbance 107
• 7.1 Problem Statement 107
• 7.2 Adaptive Neural Control Design Based on Fractional-Order Disturbance Observer 108
• 7.3 Simulation Examples 115
• 7.3.1 Fractional-Order Chaotic Electronic Oscillator 116
• 7.3.2 Fractional-OrderModified Jerk System 118
• 7.4 Conclusion 121
• 8 Stabilization Control of Continuous-Time Fractional Positive Systems Based on Disturbance Observer 123
• 8.1 Problem Statement 123
• 8.1.1 Notation and Definitions 123
• 8.1.2 Preliminaries 123
• 8.2 Main Results 126
• 8.2.1 Fractional Disturbance Observer 126
• 8.2.2 Stabilization Control of Fractional Positive System 128
• 8.2.3 Simulation of Fractional Positive System 130
• 8.2.4 Stabilization Control of Fractional Bounded Positive System 131
• 8.2.5 Simulation of Fractional Bounded Positive System 133
• 8.3 Conclusion 137
• 9 Sliding-Mode Synchronization Control for Fractional-Order Chaotic Systems with Disturbance 139
• 9.1 Problem Statement 139
• 9.2 Design of Fractional-Order Disturbance Observer 139
• 9.3 Disturbance-Observer-Based Synchronization Control of Fractional-Order Chaotic Systems 141
• 9.4 Simulation Examples 144
• 9.4.1 Synchronization Control of Modified Fractional-Order Jerk System 144
• 9.4.2 Synchronization Control of Fractional-Order Liu System 148
• 9.5 Conclusion 152
• 10 Anti-Synchronization Control for Fractional-Order Nonlinear Systems Using Disturbance Observer and Neural Networks 153
• 10.1 Problem Statement 153
• 10.2 Design of Disturbance Observer 153
• 10.3 Anti-Synchronization Control of Fractional-Order Nonlinear Systems 155
• 10.4 Simulation Examples 158
• 10.4.1 Anti-Synchronization Control of Fractional-Order Lorenz System 159
• 10.4.2 Anti-Synchronization Control of Fractional-Order Lu System 161
• 10.5 Conclusion 167
• 11 Synchronization Control for Fractional-Order Systems Subjected to Input Saturation 169
• 11.1 Problem Statement 169
• 11.2 Synchronization Control Design of Fractional-Order Systems with Input Saturation 170
• 11.3 Simulation Examples 172
• 11.3.1 Fractional-OrderModified Chua's Circuit with Sine Function 172
• 11.3.2 Fractional-Order Four-Dimensional Modified Chua's Circuit 174
• 11.4 Conclusion 179
• 12 Synchronization Control for Fractional-Order Chaotic Systems with Input Saturation and Disturbance 181
• 12.1 Problem Statement 181
• 12.2 Design of Fractional-Order Disturbance Observer 181
• 12.3 Design of Synchronization Control 183
• 12.4 Simulation Examples 185
• 12.4.1 Fractional-Order Chua's Circuit 185
• 12.4.2 Fractional-Order Hyperchaos Chua's Circuit 189
• 12.5 Conclusion 197
• Appendix A Fractional Derivatives of Some Functions 199
• A.1 Fractional Derivative of Constant 199
• A.2 Fractional Derivative of the Power Function 199
• A.3 Fractional Derivative of the Exponential Function 200
• A.4 Fractional Derivatives of Sine and Cosine Functions 201
• Appendix B Table of Caputo Derivatives 203
• Appendix C Laplace Transforms Involving Fractional Operations 205
• C.1 Laplace Transforms 205
• C.2 Special Functions for Laplace Transforms 205
• C.3 Laplace Transform Tables 205
• References 211
• Index 227.
• (source: Nielsen Book Data)

A treatise on investigating tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturation Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation provides the reader with a good understanding on how to achieve tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturation. Although some texts have touched upon control of fractional-order systems, the issues of input saturation and disturbances have rarely been considered together. This book offers chapter coverage of fractional calculus and fractional-order systems; fractional-order PID controller and fractional-order disturbance observer; design of fractional-order controllers for nonlinear chaotic systems and some applications; sliding mode control for fractional-order nonlinear systems based on disturbance observer; disturbance observer based neural control for an uncertain fractional-order rotational mechanical system; adaptive neural tracking control for uncertain fractional-order chaotic systems subject to input saturation and disturbance; stabilization control of continuous-time fractional positive systems based on disturbance observer; sliding mode synchronization control for fractional-order chaotic systems with disturbance; and more. Based on the approximation ability of the neural network (NN), the adaptive neural control schemes are reported for uncertain fractional-order nonlinear systems Covers the disturbance estimation techniques that have been developed to alleviate the restriction faced by traditional feedforward control and reject the effect of external disturbances for uncertain fractional-order nonlinear systems By combining the NN with the disturbance observer, the disturbance observer based adaptive neural control schemes have been studied for uncertain fractional-order nonlinear systems with unknown disturbances Considers, together, the issue of input saturation and the disturbance for the control of fractional-order nonlinear systems in the present of system uncertainty, external disturbance, and input saturation Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation can be used as a reference for the academic research on fractional-order nonlinear systems or used in Ph.D. study of control theory and engineering.
(source: Nielsen Book Data)

• section 1. Reconfigurable systems
• section 2. Network-on-chip
• section 3. Systems codesign

• Reconfigurable Systems Effective and Efficient Design Space Exploration for Heterogeneous Microprocessor Systems on Chip Chao Wang, Peng Chen, Xi Li, Xuda Zhou, Xuehai Zhou, and Nadia Nedjah Integer DCT-Based Real-Time Video Watermarking for H.264 Encoder Amit M. Joshi, Vivekanand Mishra, and R.M. Patrikar FPGA-Accelerated Algorithm for the Regular Expressions Matching System Pawel Russek and Kazimierz Wiatr Case Study of Genome Sequencing on an FPGA: Survey and a New Perspective Chao Wang, Peng Chen, Xi Li, Xiang Ma, Qi Yu, Xuehai Zhou, and Nadia Nedjah
• Network-on-Chip Interprocess Communication via Crossbar for Shared Memory Multiprocessor Systems on Chip Luiza de Macedo Mourelle, Nadia Nedjah, and Fabio Goncalves Pessanha Extended Quality of Service Modeling Based on Multiapplication Environment in Network on Chip Abdelkader Saadaoui and Salem Nasri Ant Colony Routing for Latency Reduction in 3D Network-on-Chips Luneque Del Rio Souza e Silva Jr., Nadia Nedjah, and Luiza de Macedo Mourelle
• Systems Codesign Codem: Software/Hardware Codesign for Embedded Multicore Systems Supporting Hardware Services Chao Wang, Xi Li, Xuehai Zhou, Nadia Nedjah, and Aili Wang Greedy Partitioning and Insert Scheduling Algorithm for Hardware-Software Codesign on MPSoCs Chao Wang, Chunsheng Li, Xi Li, Aili Wang, Fahui Jia, Xuehai Zhou, and Nadia Nedjah.
• (source: Nielsen Book Data)

Reconfigurable computing techniques and adaptive systems are some of the most promising architectures for microprocessors. Reconfigurable and Adaptive Computing: Theory and Applications explores the latest research activities on hardware architecture for reconfigurable and adaptive computing systems. The first section of the book covers reconfigurable systems. The book presents a software and hardware codesign flow for coarse-grained systems-on-chip, a video watermarking algorithm for the H.264 standard, a solution for regular expressions matching systems, and a novel field programmable gate array (FPGA)-based acceleration solution with MapReduce framework on multiple hardware accelerators. The second section discusses network-on-chip, including an implementation of a multiprocessor system-on-chip platform with shared memory access, end-to-end quality-of-service metrics modeling based on a multi-application environment in network-on-chip, and a 3D ant colony routing (3D-ACR) for network-on-chip with three different 3D topologies. The final section addresses the methodology of system codesign. The book introduces a new software-hardware codesign flow for embedded systems that models both processors and intellectual property cores as services. It also proposes an efficient algorithm for dependent task software-hardware codesign with the greedy partitioning and insert scheduling method (GPISM) by task graph.
(source: Nielsen Book Data)

• Introduction
• Preliminaries
• Underactuated System Dynamics and Coordinate Transformation
• Controller Design
• Cart Pole System
• Overhead Cranes
• TORA System
• Rotary Inverted Pendulum
• Vibration Absorber
• Pendubot
• Bibliography
• Index--.
• (source: Nielsen Book Data)

In this book, we collected recent results on the control of underactuated mechanical systems subject to internal uncertainties and external disturbances. The strategy developed is so universal that it is not restricted to a specific system but a large class of underactuated systems. Several benchmark systems are studied in this book, including detailed literature review, system dynamics derivation, control problem formulation, and simulation verification. The control strategy developed in chapter 4 is able to stabilize all these benchmark systems with satisfactory performance regardless of the underactuated dynamics and various uncertainties. The book is written as a text suitable for graduate students in the advanced course for the control of underactuated systems. It also provides valuable tools for researchers and practicing engineers working on the control of underactuated mechanical systems.
(source: Nielsen Book Data)

• Introduction.- Fundamentals of Dual Control.- Survey of Dual Control Methods.- Bicriterial Synthesis Method for Dual Controllers.- Convergence and Stability of Adaptive Dual Control.- Dual Pole-Placement Controller with Direct Adaptation.- Dual Model Reference Adaptive Control (MRAC).- Dual Control for Multivariable Systems in State Space Representation.- A Simplified Approach to the Synthesis of Dual Controllers with Indirect Adaptation.- Dual Pole-Placement and LQG Controllers with Indirect Adaptation.- Application of Dual Controllers to the Speed Control of a Thyristor-Driven DC-Motor.- Application of Dual Controllers to a Laboratory Scale Vertical Take-Off Airplane.- Robustness against Unmodeled Effects and System Stability.- Dual Modification of Predictive Adaptive Controllers.- Simulation Studies and Real-Time Control Using MATLAB/SIMULINK.- Conclusion.
• (source: Nielsen Book Data)

This monograph demonstrates how the performance of various well-known adaptive controllers can be improved significantly using the dual effect. The modifications to incorporate dual control are realized separately and independently of the main adaptive controller without complicating the algorithms. A new bicriterial approach for dual control is developed and applied to various types of popular linear and nonlinear adaptive controllers. Practical applications of the designed controllers to several real-time problems are presented. This monograph is the first book providing a complete exposition on the dual control problem from the inception in the early 1960s to the present state of the art aiming at students and researchers in adaptive control as well as design engineers in industry.
(source: Nielsen Book Data)

• Preface
• .1. Introduction
• .2. Systems Theory
• .3. Adaptive Parameter Estimation
• .4. Adaptive State Feedback Control
• .5. Continuous-Time Model Reference Adaptive Control
• .6. Discrete-Time Model Reference Adaptive Control
• .7. Indirect Adaptive Control
• .8. A Comparison Study
• .9. Multivariable Adaptive Control
• .10. Adaptive Control of Systems with Nonlinearities.Bibliography.Index.
• (source: Nielsen Book Data)

This is a systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time. Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one s understanding of adaptive control theory. "Adaptive Control Design and Analysis" features: introduction to systems and control; stability, operator norms, and signal convergence; adaptive parameter estimation; state feedback adaptive control designs; parametrization of state observers for adaptive control; unified continuous and discrete time adaptive control; L1+a robustness theory for adaptive systems; direct and indirect adaptive control designs; benchmark comparison study of adaptive control designs; multivariate adaptive control; nonlinear adaptive control; adaptive compensation of actuator nonlinearities; end of chapter discussion, problems, and advanced topics. As either a textbook or reference, this self contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike.
(source: Nielsen Book Data)

• Preface.-
• 1. N-Ocular Volume Holographic Imaging.-
• 2. Multi-Task Allocation and Path Planning for Cooperating UAVs.-
• 3. On the Construction of Virtual Backbone for Ad Hoc Wireless Network.-
• 4. Control Graphs for Robot Networks.-
• 5. Search, Classification and Attack Decisions.-
• 6. Path Planning for Unmanned Aerial Vehicles in Uncertain and Adversarial Environments.-
• 7. Automatically Synthesized Controllers for Distributed Assembly.-
• 8. The Search for the Universal Concept of Complexity and a General Optimality Condition of Cooperative Agents.-
• 9. Robust decision Making: Addressing Uncertainties in Distributions.-
• 10. Network-Centric MFA Tracking Architectures.-
• 11. Technologies Leading to Unified Multi-Agent Collection and Coordination.-
• 12. Optimal Trajectories for Cooperative Classification.-
• 13. Cooperative Control Designs for Uninhabited Air Vehicles.-
• 14. Coupling in UAV Cooperative Control.-
• 15. Optimal Adaptive Target Shooting with Imperfect Feedback Systems.
• (source: Nielsen Book Data)

During the last decades, considerable progress has been observed in all aspects regarding the study of cooperative systems, including modelling of cooperative systems, resource allocation, discrete event driven dynamical control, continuous and hybrid dynamical control, and theory of the interaction of information, control, and hierarchy. Solution methods have been proposed using control and optimization approaches, emergent rule based techniques, game theoretic and team theoretic approaches. Measures of performance have been suggested that include the effects of hierarchies and information structures on solutions, performance bounds, concepts of convergence and stability, and problem complexity. These and other topics were discussed at the Second Annual Conference on Cooperative Control and Optimization in Gainesville, Florida. Refereed papers written by selected conference participants from the conference are gathered in this volume, which presents problem models, theoretical results, and algorithms for various aspects of cooperative control. The book is addressed to faculty, graduate students, and researchers in optimization and control, computer sciences and engineering.
(source: Nielsen Book Data)

This book offers an up-close look at the theory behind and application of extremum seeking. Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today's neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, "Real-Time Optimization by Extremum-Seeking Control" presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential. Filled with in-depth insight and expert advice, "Real-Time Optimization by Extremum-Seeking Control": develops optimization theory from the points of dynamic feedback and adaptation; builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques; provides a collection of useful tools for problems in this complex area; presents numerous applications of this powerful methodology; and demonstrates the immense potential of this methodology for future theory development and applications. "Real-Time Optimization by Extremum-Seeking Control" is an important resource for both students and professionals in all areas of engineering - electrical, mechanical, aerospace, chemical, biomedical - and is also a valuable reference for practicing control engineers.
(source: Nielsen Book Data)

• Preface. I: THEORY.
• 1. SISO Scheme and Linear Analysis.
• 2. Multiparameter Extremum Seeking.
• 3. Slope Seeking.
• 4. Discrete Time Extremum Seeking.
• 5. Nonlinear Analysis.
• 6. Limit Cycle Minimization. II: APPLICATIONS.
• 7. Antilock Braking.
• 8. Bioreactors.
• 9. Formation Flight. 10.Combustion Instabilities.
• 11. Compressor Instabilities: Part I.
• 12. Compressor Instabilities: Part II. Appendix A: Continuous Time Lemmas. Appendix B: Discrete Time Lemas. Appendix C: Aircraft Dynamics in Close Formation Flight. Appendix D: Derivation of (11.8) and (11.10). Appendix E: Derivation of the Critical Slopes. Appendix F: Proof of Lemma 11
• .1. Bibliography. Index.
• (source: Nielsen Book Data)

An up-close look at the theory behind and application of extremum seeking Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today's neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, Real-Time Optimization by Extremum-Seeking Control presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential. Filled with in-depth insight and expert advice, Real-Time Optimization by Extremum-Seeking Control: Develops optimization theory from the points of dynamic feedback and adaptation Builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques Provides a collection of useful tools for problems in this complex area Presents numerous applications of this powerful methodology Demonstrates the immense potential of this methodology for future theory development and applications Real-Time Optimization by Extremum-Seeking Control is an important resource for both students and professionals in all areas of engineering-electrical, mechanical, aerospace, chemical, biomedical-and is also a valuable reference for practicing control engineers.
(source: Nielsen Book Data)

• Adaptive Tuning Methods of the Foxboro I/A System
• The Exploitation of Adaptive Modelling in the Model Predictive Control Environment of Connoisseur
• Adaptive Predictive Regulatory Control with BrainWave (TM)
• Model-Free Adaptive Control
• Expert-Based Adaptive Control - ControlSoft's INTUNE Adaptive and Diagnostic Software
• KnowledgeScape, an Object-oriented Real-time Adaptive Modeling and Optimization Expert Control System for the Process Industries.
• (source: Nielsen Book Data)

Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how it works, and reasons why a user would want it as well as an in depth explanation of their particular method. This is one of the latest technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human intervention. Rather than the common academic-based approach that books on this subject generally take, the contributions here outline practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available.
(source: Nielsen Book Data)

• Adaptive Tuning Methods of the Foxboro I/A System
• The Exploitation of Adaptive Modelling in the Model Predictive Control Environment of Connoisseur
• Adaptive Predictive Regulatory Control with BrainWave (TM)
• Model-Free Adaptive Control
• Expert-Based Adaptive Control - ControlSoft's INTUNE Adaptive and Diagnostic Software
• KnowledgeScape, an Object-oriented Real-time Adaptive Modeling and Optimization Expert Control System for the Process Industries.
• (source: Nielsen Book Data)

Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how it works, and reasons why a user would want it as well as an in depth explanation of their particular method. This is one of the latest technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human intervention. Rather than the common academic-based approach that books on this subject generally take, the contributions here outline practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available.
(source: Nielsen Book Data)

• Recurrent high-order neural network (RHONN) structure and approximation capabilities
• indirect adaptive control
• direct adaptive control
• manufacturing sytems scheduling
• scheduling using RHONNs - a test case.
• (source: Nielsen Book Data)

The primary purpose of this book is to present a set of techniques which allow the design of controllers able to guarantee stability, convergence and robustness for dynamical systems with unknown nonlinearities and of manufacturing systems.To compensate for the significant amount of uncertainty in system structure, a neural network model developed recently, namely the Recurrent High Order Neural Network (RHONN), is employed.Real applications are provided with illustrations and tables for clarification; the book contains material on:- RHONN structure and approximation capabilities- indirect adaptive control- direct adaptive control- scheduling for manufacturing systems- test case for scheduling using RHONNs.The book is primarily intended for industrial and institutional practitioners but should be of significant interest to undergraduate and graduate students and academic scientists working with neural networks and their applications in engineering.
(source: Nielsen Book Data)

Synergy and Duality of Identification and Control examines the relationship between modelling and control of dynamic systems. Both stochastic and worst-case design approaches are presented. System identification is introducted in worst-case and stochastic frameworks. Interaction between modelling and control is studied at four levels: separate identification and control design, iterative identification and control design, dual control and synergistic interaction of modelling and control. The last part of the book focuses on fast learning control systems via parametric models. This comprehensive monograph is equally suitable for graduate students as well as for researchers in the fields of control engineering and digital signal processing.
(source: Nielsen Book Data)

• List of contributors
• Preface
• Adaptive internal model control
• An algorithm for robust adaptive control with less prior knowledge
• Adaptive variable structure control
• Indirect adaptive periodic control
• Adaptive stabilization of uncertain discrete-time systems via switching control: the method of localization
• Adaptive nonlinear control: passivation and small gain techniques
• Active identification for control of discrete-time uncertain nonlinear systems
• Optimal adaptive tracking for nonlinear systems
• Stable adaptive systems in the presence of nonlinear parametrization
• Adaptive inverse for actuator compensation
• Stable multi-input multi-output adaptive fuzzy/neural control
• Adaptive robust control scheme with an application to PM synchronous motors
• Index.
• (source: Nielsen Book Data)

Adaptive control is no longer just an important theoretical field of study, but is also providing solutions to real-world problems. Adaptive techniques will transform the world of control. The leading world practitioners of adaptive control have contributed to this handbook which is the most important work yet in this field. Not only are techniques described in theory, but detailed control algorithms are given, making this a practical cookbook of adaptive control for both control professionals and practising engineers. This book presents the most advanced techniques and algorithms of adaptive control. These include various robust techniques, performance enhancement techniques, techniques with less a-priori knowledge, nonlinear adaptive control techniques and intelligent adaptive techniques. Each technique described has been developed to provide a practical solution to a real-life problem. This volume will therefore not only advance the field of adaptive control as an area of study, but will also show how the potential of this technology can be realised and offer significant benefits. This practical cookbook of adaptive control contains important research.
(source: Nielsen Book Data)

• Introduction to Adaptive Control.- Discrete-time Systems Models for Control.- Parameter Adaption Algorithms - Deterministic Environment.- Parameter Adaption Algorithms in Stochastic Environment.- Recursive Plant Model in the Context of System Identification.- Adaptive Prediction.- Digital Control Strategies.- Robust Digital Control Design.- Closed Loop.- Direct Adaptive Control.- Indirect Self-tuning and Adaptive Control.- Robust Adaptive Control.- Practical Aspects.- Perspective View.- Appendix.
• (source: Nielsen Book Data)

Adaptive Control provides techniques for the automatic adjustment in real time of controller parameters. Their purpose is to achieve or maintain a desired level of system performance when process parameters are unknown or variable. Such techniques operate by extracting significative information from real data in order to tune the controller and they feature a mechanism for adjusting parameters. The book explores both established ideas and recent trends in the field of adaptive control. More specifically, the book covers synthesis and analysis of parameter adaptation algorithms, robust digital control and recursive digital control in open and closed loop. This book considers the problems and seeks to find answers using mathematical sequences.To guide the reader, the book contains various applications of adaptive control techniques.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Basic Theory of Simple Adaptive Control
• Appendices
• 3. Extensions of the Basic Adaptive Algorithm: Alleviation of the SPR Constraints
• Appendices
• 4. Robust Design Procedures
• Appendices
• 5. Adaptive Control of Time-Varying and Nonlinear Systems
• Appendices
• 6. Design of Model Reference Adaptive Controllers
• Appendices
• 7. Case Studies
• References
• Index.
• (source: Nielsen Book Data)

Suitable either as a reference for practicing engineers or as a text for a graduate course in adaptive control systems, this book is a self-contained compendium of readily implementable adaptive control algorithms that have been developed and applied by the authors for over fifteen years. These algorithms, which do not require the user to identify the process parameters explicitly, have been successfully applied to a wide variety of engineering problems including flexible structure control, blood pressure control, and robotics; they are suitable for a wide variety of multiple input-output control systems with uncertainity and external disturbances. The text is intended to enable anyone with knowledge of basic linear multivariable systems to adapt the algorithms to problems in a wide variety of disciplines. Thus, in addition to developing the theoretical details of the algorithms presented, the text gives considerable emphasis to design of algorithms and to representative applications in flight control, flexible structure control, robotics, and drug-infusion control. Engineers can thus use and test these algorithms in practical problems. This second edition has been corrected and updated throughout. It makes use of MATLAB programs for some of the illustrative examples; these programs are described in the text and can be obtained from the MathWorks file server.
(source: Nielsen Book Data)