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Adaptive Control of Dynamic Systems with Uncertainty and Quantization (Automation and Control Engineering)
by Jing Zhou Lantao Xing Changyun WenThis 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.
Adaptive Control of Solar Energy Collector Systems (Advances in Industrial Control)
by Rui Neves-Silva João M. Lemos José M. IgrejaThis book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants: they are distributed-parameter systems, i. e. , systems with dynamics that depend on space as well as time; their dynamics is nonlinear, with a bilinear structure; there is a significant level of uncertainty in plant knowledge. Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts of the text are devoted to design methods that assume only a very limited knowledge about the plant. Other parts detail methods that rely on knowledge of the dominant plant structure. These methods are more plant specific, but allow the improvement of performance. Adaptive Control of Solar Energy Collector Systems demonstrates the dynamics of solar fields to be rich enough to present a challenge to the control designer while, at the same time, simple enough to allow analytic work to be done, providing case studies on dynamics and nonlinear control design in a simple and revealing, but nontrivial way. The control approaches treated in this monograph can be generalized to apply to other plants modelled by hyperbolic partial differential equations, especially process plants in which transport phenomena occur, plants like dryers, steam super-heaters and even highway traffic. An important example, used repeatedly throughout the text, is a distributed-collector solar field installed at Plataforma Solar de Almeria, located in southern Spain. The control algorithms laid out in the text are illustrated with experimental results generated from this plant. Although the primary focus of this monograph is solar energy collector, the range of other systems which can benefit from the methods described will make it of interest to control engineers working in many industries as well as to academic control researchers interested in adaptive control and its applications.
Adaptive Control Systems: Techniques and Applications (Electrical And Computer Engineering Ser. #39)
by Chalamimpossible to access. It has been widely scattered in papers, reports, and proceedings ofsymposia, with different authors employing different symbols and terms. But now thereis a book that covers all aspects of this dynamic topic in a systematic manner.Featuring consistent terminology and compatible notation, and emphasizing unifiedstrategies, Adaptive Control Systems provides a comprehensive, integrated accountof basic concepts, analytical tools, algorithms, and a wide variety of application trendsand techniques.Adaptive Control Systems deals not only with the two principal approachesmodelreference adaptive control and self-tuning regulators-but also considers otheradaptive strategies involving variable structure systems, reduced order schemes, predictivecontrol, fuzzy logic, and more. In addition, it highlights a large number of practical applicationsin a range of fields from electrical to biomedical and aerospace engineering ...and includes coverage of industrial robots.The book identifies current trends in the development of adaptive control systems ...delineates areas for further research . : . and provides an invaluable bibliography of over1,200 references to the literature.The first authoritative reference in this important area of work, Adaptive ControlSystems is an essential information source for electrical and electronics, R&D,chemical, mechanical, aerospace, biomedical, metallurgical, marine, transportation, andpower plant engineers. It is also useful as a text in professional society seminars and inhousetraining programs for personnel involved with the control of complex systems, andfor graduate students engaged in the study of adaptive control systems.
Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems (Studies in Systems, Decision and Control #167)
by Ding Wang Chaoxu MuThis book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.
Adaptive Detection for Multichannel Signals in Non-Ideal Environments
by Weijian Liu Zeyu Wang Hongmeng ChenThis book systematically presents adaptive multichannel signal detection in three types of non-ideal environments, including sample-starved scenarios, signal mismatch scenarios, and noise plus subspace interference environments.The authors provide definitions of key concepts, detailed derivations of adaptive multichannel signal detectors, and specific examples for each non-ideal environment. In addition, the possible future trend of adaptive detection methods is discussed, as well as two further research points – namely, the adaptive detection algorithms based on information geometry, and the hybrid approaches that combine adaptive detection algorithms with machine learning algorithms.The book will be of interest to researchers, advanced undergraduates, and graduate students in sonar, radar signal processing, and communications engineering.
Adaptive Detection of Multichannel Signals Exploiting Persymmetry
by Jun Liu Danilo Orlando Chengpeng Hao Weijian LiuThis book offers a systematic presentation of persymmetric adaptive detection, including detector derivations and the definition of key concepts, followed by detailed discussion relating to theoretical underpinnings, design methodology, design considerations, and techniques enabling its practical implementation. The received data for modern radar systems are usually multichannel, namely, vector-valued, or even matrix-valued. Multichannel signal detection in Gaussian backgrounds is a fundamental problem for radar applications. With an overarching focus on persymmetric adaptive detectors, this book presents the mathematical models and design principles necessary for analyzing the behavior of each kind of persymmetric adaptive detector. Building upon that, it also introduces new design approaches and techniques that will guide engineering students as well as radar engineers toward efficient detector solutions, especially in challenging sample-starved environments where training data are limited. This book will be of interest to students, scholars, and engineers in the field of signal processing. It will be especially useful for those who have a solid background in statistical signal processing, multivariate statistical analysis, matrix theory, and mathematical analysis.
Adaptive Digital Circuits for Power-Performance Range beyond Wide Voltage Scaling: From the Clock Path to the Data Path
by Massimo Alioto Saurabh Jain Longyang LinThis book offers the first comprehensive coverage of digital design techniques to expand the power-performance tradeoff well beyond that allowed by conventional wide voltage scaling. Compared to conventional fixed designs, the approach described in this book makes digital circuits more versatile and adaptive, allowing simultaneous optimization at both ends of the power-performance spectrum. Drop-in solutions for fully automated and low-effort design based on commercial CAD tools are discussed extensively for processors, accelerators and on-chip memories, and are applicable to prominent applications (e.g., IoT, AI, wearables, biomedical). Through the higher power-performance versatility techniques described in this book, readers are enabled to reduce the design effort through reuse of the same digital design instance, across a wide range of applications. All concepts the authors discuss are demonstrated by dedicated testchip designs and experimental results. To make the results immediately usable by the reader, all the scripts necessary to create automated design flows based on commercial tools are provided and explained.
Adaptive Digital Filters
by Zoran Banjac Milan Milosavljević Branko Kovačević"Adaptive Digital Filters" presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in mastering this important field.
Adaptive Digital Filters (Signal Processing and Communications)
by Maurice BellangerThis text emphasizes the intricate relationship between adaptive filtering and signal analysis - highlighting stochastic processes, signal representations and properties, analytical tools, and implementation methods. This second edition includes new chapters on adaptive techniques in communications and rotation-based algorithms. It provides practical applications in information, estimation, and circuit theories.
Adaptive Disaster Risk Assessment: Combining Multi-Hazards with Socioeconomic Vulnerability and Dynamic Exposure (IHE Delft PhD Thesis Series)
by Neiler Medina PenaClimate change, combined with the rapid and often unplanned urbanisation trends, is associated with a rising trend in the frequency and severity of disasters triggered by natural hazards. In order to face the impacts of such threats, it is necessary to have an appropriate Disaster Risk Assessment (DRA). Traditional DRA approaches for disaster risk reduction (DRR) have focused mainly on the hazard component of risk, with little attention to the vulnerability and the exposure components. To address this issue, this dissertation’s main objective is to develop and test a disaster risk modelling framework that incorporates socioeconomic vulnerability and the adaptive nature of exposure associated with human behaviour in extreme hydro-meteorological events in the context of SIDS. To achieve the objective, an Adaptive Disaster Risk Assessment (ADRA) framework is proposed. ADRA uses an index-based approach (PeVI) to assess the socioeconomic vulnerability using three components: susceptibility, lack of coping capacities, and lack of adaptation. Furthermore, ADRA explicitly incorporates the exposure component using two approaches; first, a logistic regression model was built using the actual evacuation rates observed during Hurricane Irma, and second, an Agent-based model is used to simulate how households change their exposure levels in relation to different sources of information
Adaptive, Dynamic, and Resilient Systems
by Niranjan Suri Giacomo CabriAs the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of netwo
Adaptive Dynamic Programming: For Chemotherapy Drug Delivery
by Jiayue Sun Shun Xu Yang Liu Huaguang ZhangThis open access book focuses on the practical application of Adaptive Dynamic Programming (ADP) in chemotherapy drug delivery, taking into account clinical variables and real-time data. ADP's ability to adapt to changing conditions and make optimal decisions in complex and uncertain situations makes it a valuable tool in addressing pressing challenges in healthcare and other fields. As optimization technology evolves, we can expect to see even more sophisticated and powerful solutions emerge.
Adaptive Dynamic Programming for Control: Algorithms and Stability (Communications and Control Engineering)
by Yanhong Luo Huaguang Zhang Ding Wang Derong LiuThere are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: * infinite-horizon control for which the difficulty of solving partial differential Hamilton-Jacobi-Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; * finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; * nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: * establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; * demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and * shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.
Adaptive Dynamic Programming with Applications in Optimal Control (Advances in Industrial Control)
by Ding Wang Derong Liu Qinglai Wei Xiong Yang Hongliang LiThis book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP approach which is then extended to other branches of control theory including decentralized control, robust and guaranteed cost control, and game theory. In the last part of the book the real-world significance of ADP theory is presented, focusing on three application examples developed from the authors' work: * renewable energy scheduling for smart power grids; * coal gasification processes; and * water-gas shift reactions. Researchers studying intelligent control methods and practitioners looking to apply them in the chemical-process and power-supply industries will find much to interest them in this thorough treatment of an advanced approach to control.
Adaptive Educational Technologies for Literacy Instruction
by Scott A. Crossley Danielle S. McNamaraWhile current educational technologies have the potential to fundamentally enhance literacy education, many of these tools remain unknown to or unused by today’s practitioners due to a lack of access and support. Adaptive Educational Technologies for Literacy Instruction presents actionable information to educators, administrators, and researchers about available educational technologies that provide adaptive, personalized literacy instruction to students of all ages. These accessible, comprehensive chapters, written by leading researchers who have developed systems and strategies for classrooms, introduce effective technologies for reading comprehension and writing skills.
Adaptive Feed-Forward Control of Low Frequency Interior Noise (Intelligent Systems, Control and Automation: Science and Engineering #56)
by Thomas KletschkowskiThis book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.
Adaptive Filtering: Algorithms and Practical Implementation (The\springer International Series In Engineering And Computer Science Ser. #694)
by Paulo S. DinizIn the fifth edition of this textbook, author Paulo S.R. Diniz presents updated text on the basic concepts of adaptive signal processing and adaptive filtering. He first introduces the main classes of adaptive filtering algorithms in a unified framework, using clear notations that facilitate actual implementation. Algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Examples address up-to-date problems drawn from actual applications. Several chapters are expanded and a new chapter ‘Kalman Filtering’ is included. The book provides a concise background on adaptive filtering, including the family of LMS, affine projection, RLS, set-membership algorithms and Kalman filters, as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Problems are included at the end of chapters. A MATLAB package is provided so the reader can solve new problems and test algorithms. The book also offers easy access to working algorithms for practicing engineers.
Adaptive Filtering: Algorithms and Practical Implementation (The\springer International Series In Engineering And Computer Science Ser. #694)
by Paulo S. R. DinizIn the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S. R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are included at the end of chapters, and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test algorithms in a quick manner. Additionally, the book provides easy access to working algorithms for practicing engineers.
Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® (Electrical Engineering Primer Ser.)
by Alexander D. PoularikasAdaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area—the least mean square (LMS) adaptive filter. This largely self-contained text: Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton’s algorithm Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples Delivers a concise introduction to MATLAB®, supplying problems, computer experiments, and more than 110 functions and script files Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems.
Adaptive Filtering Prediction and Control
by Kwai Sang Sin Graham C GoodwinThis unified survey of the theory of adaptive filtering, prediction, and control focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms.Ideal for advanced undergraduate and graduate classes, this treatment consists of two parts. The first section concerns deterministic systems, covering models, parameter estimation, and adaptive prediction and control. The second part examines stochastic systems, exploring optimal filtering and prediction, parameter estimation, adaptive filtering and prediction, and adaptive control. Extensive appendices offer a summary of relevant background material, making this volume largely self-contained. Readers will find that these theories, formulas, and applications are related to a variety of fields, including biotechnology, aerospace engineering, computer sciences, and electrical engineering.
Adaptive Filtering Primer with MATLAB
by Alexander D. Poularikas Zayed M. Ramadan<p>Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fundamentals of this field was necessary. The material and the principles presented in this book are easily accessible to engineers, scientists, and students who would like to learn the fundamentals of this field and have a background at the bachelor level. <p>Adaptive Filtering Primer with MATLAB clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage. <p>With applications across a wide range of areas, including radar, communications, control, medical instrumentation, and seismology, Adaptive Filtering Primer with MATLAB is an ideal companion for quick reference and a perfect, concise introduction to the field.</p>
Adaptive Filtering Under Minimum Mean p-Power Error Criterion
by Badong Chen Wentao MaAdaptive filtering still receives attention in engineering as the use of the adaptive filter provides improved performance over the use of a fixed filter under the time-varying and unknown statistics environments. This application evolved communications, signal processing, seismology, mechanical design, and control engineering. The most popular optimization criterion in adaptive filtering is the well-known minimum mean square error (MMSE) criterion, which is, however, only optimal when the signals involved are Gaussian-distributed. Therefore, many "optimal solutions" under MMSE are not optimal. As an extension of the traditional MMSE, the minimum mean p-power error (MMPE) criterion has shown superior performance in many applications of adaptive filtering. This book aims to provide a comprehensive introduction of the MMPE and related adaptive filtering algorithms, which will become an important reference for researchers and practitioners in this application area. The book is geared to senior undergraduates with a basic understanding of linear algebra and statistics, graduate students, or practitioners with experience in adaptive signal processing.Key Features: Provides a systematic description of the MMPE criterion. Many adaptive filtering algorithms under MMPE, including linear and nonlinear filters, will be introduced. Extensive illustrative examples are included to demonstrate the results.
Adaptive Filters
by Behrouz Farhang-BoroujenyThis second edition of Adaptive Filters: Theory and Applications has been updated throughout to reflect the latest developments in this field; notably an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years. The book offers an easy to understand approach to the theory and application of adaptive filters by clearly illustrating how the theory explained in the early chapters of the book is modified for the various applications discussed in detail in later chapters. This integrated approach makes the book a valuable resource for graduate students; and the inclusion of more advanced applications including antenna arrays and wireless communications makes it a suitable technical reference for engineers, practitioners and researchers. Key features:* Offers a thorough treatment of the theory of adaptive signal processing; incorporating new material on transform domain, frequency domain, subband adaptive filters, acoustic echo cancellation and active noise control.* Provides an in-depth study of applications which now includes extensive coverage of OFDM, MIMO and smart antennas.* Contains exercises and computer simulation problems at the end of each chapter.* Includes a new companion website hosting MATLAB® simulation programs which complement the theoretical analyses, enabling the reader to gain an in-depth understanding of the behaviours and properties of the various adaptive algorithms.
Adaptive Governance and Water Conflict: New Institutions for Collaborative Planning
by John T. Scholz Bruce StiftelWater policy seems in perpetual crisis. Increasingly, conflicts extend beyond the statutory authority, competence, geographical jurisdictions, and political constituencies of highly specialized governing authorities. While other books address specific policy approaches or the application of adaptive management strategies to specific problems, this is the first book to focus more broadly on adaptive governance, or the evolution of new institutions that attempt to resolve conflicts among competing authorities. Adaptive Governance and Water Conflict investigates new types of water conflicts among users in the seemingly water-rich Eastern United States. Eight case studies of water quality, water quantity, and habitat preservation or restoration in Florida were chosen to span the range of conflicts crossing fragmented regulatory boundaries. Each begins with a history of the conflict and then focuses on the innovative institutional arrangements - some successful, some not - that evolved to grapple with the resulting challenges. In the chapters that follow, scholars and practitioners in urban planning, political science, engineering, law, policy, administration, and geology offer different theoretical and experience-based perspectives on the cases. Together, they discuss five challenges that new institutions must overcome to develop sustainable solutions for water users: Who is to be involved in the policy process? How are they to interact? How is science to be used? How are users and the public to be made aware? How can solutions be made efficient and equitable? In its diverse perspectives and unique combination of theory, application, and analysis, Adaptive Governance and Water Conflict will be a valuable book for water professionals, policy scientists, students, and scholars in natural resource planning and management.
Adaptive Governance in Carbon Farming Policies
by Nooshin TorabiThis book discusses a variety of different perspectives involved in biodiversity management and bio-sequestration projects in Australia, working towards achieving adaptive governance in carbon farming. It not only examines landholders’ motivation but also the challenges of integrating biodiverse forests into the agricultural landscape. Drawing on the contrast between science and policy stakeholders’ views on carbon farming and the practical challenges of achieving adaptive governance, the book discusses the significant gap between theory and practice encountered in this field of study. The book suggests ways of improving the decision-making capacity of government officials and policymakers involved in managing carbon and biodiversity markets, as well as introducing measures to promote adaptive governance by engaging landholders in more effective land conservation. Climate change is a pressing issue on the global political agenda, and this book makes an important contribution to the ongoing debate. This book will be an invaluable reference for practitioners, policymakers and researchers interested in alternative forms of governance in natural resource management.