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This book illustrates the application of fractional calculus in crowd dynamics via modeling and control groups of pedestrians. Decision-making processes, conservation laws of mass/momentum, and micro-macro models are employed to describe system dynamics while cooperative movements in micro scale, and fractional diffusion in macro scale are studied to control the group of pedestrians. Obtained work is included in the Intelligent Evacuation Systems that is used for modeling and to control crowds of pedestrians. With practical issues considered, this book is of interests to mathematicians, physicists, and engineers.

Pedestrian traffic flow --- Fractional calculus. --- MATHEMATICS / Differential Equations. --- MATHEMATICS / Mathematical Analysis. --- MATHEMATICS / Calculus. --- MATHEMATICS / Applied. --- Derivatives and integrals, Fractional --- Differentiation of arbitrary order, Integration and --- Differintegration, Generalized --- Fractional derivatives and integrals --- Generalized calculus --- Generalized differintegration --- Integrals, Fractional derivatives and --- Integration and differentiation of arbitrary order --- Calculus --- Pedestrians --- Traffic flow --- Mathematical models. --- E-books

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Precision farming. --- Evapotranspiration --- Drone aircraft in remote sensing. --- Measurement. --- Drone remote sensing --- Remote sensing --- Consumptive use --- Water-supply --- Evaporation (Meteorology) --- Plants --- Precision agriculture --- Prescription farming --- Site-specific agriculture --- Site-specific farming --- Soil specific crop management --- Agriculture --- Transpiration --- Water requirements --- Evapotranspiració --- Agricultura de precisió --- Teledetecció --- Drons

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Distributed-order differential equations, a generalization of fractional calculus, are of increasing importance in many fields of science and engineering from the behaviour of complex dielectric media to the modelling of nonlinear systems. This Brief will broaden the toolbox available to researchers interested in modeling, analysis, control and filtering. It contains contextual material outlining the progression from integer-order, through fractional-order to distributed-order systems. Stability issues are addressed with graphical and numerical results highlighting the fundamental differences between constant-, integer-, and distributed-order treatments. The power of the distributed-order model is demonstrated with work on the stability of noncommensurate-order linear time-invariant systems. Generic applications of the distributed-order operator follow: signal processing and viscoelastic damping of a mass–spring set up. A new general approach to discretization of distributed-order derivatives and integrals is described. The Brief is rounded out with a consideration of likely future research and applications and with a number of MATLAB® codes to reduce repetitive coding tasks and encourage new workers in distributed-order systems.

Dynamics. --- System analysis. --- Mechanical Engineering --- Engineering & Applied Sciences --- Mechanical Engineering - General --- Fractional calculus. --- Derivatives and integrals, Fractional --- Differentiation of arbitrary order, Integration and --- Differintegration, Generalized --- Fractional derivatives and integrals --- Generalized calculus --- Generalized differintegration --- Integrals, Fractional derivatives and --- Integration and differentiation of arbitrary order --- Engineering. --- Energy. --- System theory. --- Control engineering. --- Control. --- Systems Theory, Control. --- Signal, Image and Speech Processing. --- Energy, general. --- Calculus --- Systems theory. --- Control and Systems Theory. --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Systems, Theory of --- Systems science --- Science --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Philosophy

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This monograph provides an accessible introduction to the regional analysis of fractional diffusion processes. It begins with background coverage of fractional calculus, functional analysis, distributed parameter systems and relevant basic control theory. New research problems are then defined in terms of their actuation and sensing policies within the regional analysis framework. The results presented provide insight into the control-theoretic analysis of fractional-order systems for use in real-life applications such as hard-disk drives, sleep stage identification and classification, and unmanned aerial vehicle control. The results can also be extended to complex fractional-order distributed-parameter systems and various open questions with potential for further investigation are discussed. For instance, the problem of fractional order distributed-parameter systems with mobile actuators/sensors, optimal parameter identification, optimal locations/trajectory of actuators/sensors and regional actuation/sensing configurations are of great interest. The book’s use of illustrations and consistent examples throughout helps readers to understand the significance of the proposed fractional models and methodologies and to enhance their comprehension. The applications treated in the book run the gamut from environmental science to national security. Academics and graduate students working with cyber-physical and distributed systems or interested in the the applications of fractional calculus will find this book to be an instructive source of state-of-the-art results and inspiration for further research.

Diffusion processes. --- Cooperating objects (Computer systems) --- Distributed parameter systems. --- Engineering. --- Operator theory. --- System theory. --- Control engineering. --- Control. --- Operator Theory. --- Systems Theory, Control. --- Systems, Distributed parameter --- Control theory --- Engineering systems --- System analysis --- Markov processes --- Systems theory. --- Control and Systems Theory. --- Functional analysis --- Systems, Theory of --- Systems science --- Science --- Control engineering --- Control equipment --- Engineering instruments --- Automation --- Programmable controllers --- Philosophy

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This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledge of the system to be controlled and; second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergence is often essential. Iterative Learning Control takes account of the recently-developed comprehensive approach to robust ILC analysis and design established to handle the situation where the plant model is uncertain. Considering ILC in the iteration domain, it presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. Topics include: • Use of a lifting technique to convert the two-dimensional ILC system, which has dynamics in both the time and iteration domains, into the supervector framework, which yields a one-dimensional system, with dynamics only in the iteration domain. • Development of iteration-domain uncertainty models in the supervector framework. • ILC design for monotonic convergence when the plant is subject to parametric interval uncertainty in its Markov matrix. • An algebraic H-infinity design methodology for ILC design when the plant is subject to iteration-domain frequency uncertainty. • Development of Kalman-filter-based ILC algorithms when the plant is subject to iteration-domain stochastic uncertainties. • Analytical determination of the base-line error of ILC algorithms. • Solutions to three fundamental robust interval computational problems (used as basic tools for designing robust ILC controllers): finding the maximum singular value of an interval matrix, determining the robust stability of interval polynomial matrix, and obtaining the power of an interval matrix. Iterative Learning Control will be of great interest to academic researchers in control theory and to industrial control engineers working in robotics-oriented manufacturing and batch-processing-based industries. Graduate students of intelligent control will also find this volume instructive.

Engineering. --- Artificial intelligence. --- Bioinformatics. --- System theory. --- Control engineering. --- Robotics. --- Mechatronics. --- Biomedical engineering. --- Control. --- Systems Theory, Control. --- Artificial Intelligence (incl. Robotics). --- Control, Robotics, Mechatronics. --- Biomedical Engineering. --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Automation --- Machine theory --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Systems, Theory of --- Systems science --- Science --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Philosophy --- Data processing --- Intelligent control systems. --- Iterative methods (Mathematics) --- Iteration (Mathematics) --- Numerical analysis --- Intelligent control --- Intelligent controllers --- Automatic control --- Control and Systems Theory. --- Artificial Intelligence. --- Biomedical Engineering and Bioengineering. --- Systems theory.