Robust Sliding Mode Protocols For Formation Of Quadcopter Swarm

This book presents several robust sliding mode protocols for achieving the formation and tracking of Quadcopter swarm for a given pattern. In entire book, the concept of leader-follower formation control of a multi-agent system is exploited for deriving the protocols and the graph theory is used to represent the communication between the Quadcopters. The book covers two types of formation protocols of the Quadcopter swarm namely, continuous-time sliding mode protocols and discrete-time sliding mode protocols. First, the continuous-time higher order sliding mode protocols using super-twisting algorithm are designed for formation using linear and non-linear models of Quadcopter. Then, the discrete-time sliding mode protocols using power rate reaching law, discrete-time super twisting algorithm, and exponential reaching law are presented. The protocols are thoroughly analysed for robustness, chattering, control effort, and convergence time for achieving the formation. Also, the stability conditions using the Lyapunov function are derived to ensure the stability of the swarm with each protocol. Further, each chapter includes extensive simulation and comparative studies to show the efficacy of each protocol. The book will be useful to graduate students, research scholars, and professionals working in the domain of civilian and military usage of the drone technology.

The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.

This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircraft. It covers a range of topics, including, but not limited to, intelligent computing communication and control; new methods of navigation, estimation, and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation, and control of miniature aircraft; and sensor systems for guidance, navigation, and control. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEWTM toolkit, downloadable from the book’s page at springer.com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.

The development of algebraic geometry over groups, geometric group theory and group-based cryptography, has led to there being a tremendous recent interest in infinite group theory. This volume presents a good collection of papers detailing areas of current interest. Contents: Groups with the Weak Minimal Condition on Non-Permutable Subgroups (Laxmi K Chatuat and Martyn R Dixon)A Survey: Shamir Threshold Scheme and Its Enhancements (Chi Sing Chum, Benjamin Fine, and Xiaowen Zhang)The Zappa-Szep Product of Left-Orderable Groups (Fabienne Chouraqui)Totally Disconnected Groups From Baumslag-Solitar Groups (Murray Elder and George Willis)Elementary and Universal Theories of Nonabelian Commutative Transitive and CSA Groups (B Fine, A M Gaglione, and D Spellman)Commutative Transitivity and the CSA Property (Benjamin Fine, Anthony Gaglione, Gerhard Rosenberger, and Dennis Spellman)The Universal Theory of Free Burnside Groups of Large Prime Exponent (Anthony M Gaglione, Seymour Lipschutz, and Dennis Spellman)Primitive Curve Lengths on Pairs of Pants (Jane Gilman)Drawing Inferences Under Maximum Entropy From Relational Probabilistic Knowledge Using Group Theory (Gabriele Kern-Isberner, Marco Wilhelm, and Christoph Beierle)On Some Infinite-Dimensional Linear Groups and the Structure of Related Modules (L A Kurdachenko and I Ya Subbotin)On New Analogs of Some Classical Group Theoretical Results in Lie Rings (L A Kurdachenko, A A Pypka and I Ya Subbotin)Log-Space Complexity of the Conjugacy Problem in Wreath Products (Alexei Myasnikov, Svetla Vassileva, and Armin Weiss)Group Presentations, Cayley Graphs and Markov Processes (Peter Olszewski) Readership: Graduate students and researchers in group theory. Keywords: Infinite Group Theory;Combinatorial Group Theory;Geometric Group TheoryReview: Key Features: This book is centered on infinite group theory from a combinatorial and geometric point of view. It also contains material on non-commutative algebraic group-based cryptography

This monograph introduces recent developments in formation control of distributed-agent systems. Eschewing the traditional concern with the dynamic characteristics of individual agents, the book proposes a treatment that studies the formation control problem in terms of interactions among agents including factors such as sensing topology, communication and actuation topologies, and computations. Keeping pace with recent technological advancements in control, communications, sensing and computation that have begun to bring the applications of distributed-systems theory out of the industrial sphere and into that of day-to-day life, this monograph provides distributed control algorithms for a group of agents that may behave together. Unlike traditional control laws that usually require measurements with respect to a global coordinate frame and communications between a centralized operation center and agents, this book provides control laws that require only relative measurements and communications between agents without interaction with a centralized operator. Since the control algorithms presented in this book do not require any global sensing and any information exchanges with a centralized operation center, they can be realized in a fully distributed way, which significantly reduces the operation and implementation costs of a group of agents. Formation Control will give both students and researchers interested in pursuing this field a good grounding on which to base their work.