Explore the vast range of titles available.

In this paper, the quasi-projective synchronization of distributed-order recurrent neural networks is investigated. Firstly, based on the definition of the distributed-order derivative and metric space theory, two distributed-order differential inequalities are obtained. Then, by employing the Lyapunov method, Laplace transform, Laplace final value theorem, and some inequality techniques, the quasi-projective synchronization sufficient conditions for distributed-order recurrent neural networks are established in cases of feedback control and hybrid control schemes, respectively. Finally, two numerical examples are given to verify the effectiveness of the theoretical results.

Autonomous unmanned air vehicles (UAVs) are critical to current and future military, civil, and commercial operations. Despite their importance, no previous textbook has accessibly introduced UAVs to students in the engineering, computer, and science disciplines--until now. Small Unmanned Aircraft provides a concise but comprehensive description of the key concepts and technologies underlying the dynamics, control, and guidance of fixed-wing unmanned aircraft, and enables all students with an introductory-level background in controls or robotics to enter this exciting and important area. The authors explore the essential underlying physics and sensors of UAV problems, including low-level autopilot for stability and higher-level autopilot functions of path planning. The textbook leads the student from rigid-body dynamics through aerodynamics, stability augmentation, and state estimation using onboard sensors, to maneuvering through obstacles. To facilitate understanding, the authors have replaced traditional homework assignments with a simulation project using the MATLAB/Simulink environment. Students begin by modeling rigid-body dynamics, then add aerodynamics and sensor models. They develop low-level autopilot code, extended Kalman filters for state estimation, path-following routines, and high-level path-planning algorithms. The final chapter of the book focuses on UAV guidance using machine vision. Designed for advanced undergraduate or graduate students in engineering or the sciences, this book offers a bridge to the aerodynamics and control of UAV flight.

This chapter introduces the Laplace transform and the representation of dynamic systems in the Laplace domain. Key properties of Laplace transforms are described, such as pole and zero placement, and their influence on system behavior is shown.

The study of the local fractional Laplace transform operator based upon the local fractional calculus is addressed in this chapter. Our attentions are focused on the basic properties and theorems of the local fractional Laplace transform operator and potential applications, such as signal analysis, ODEs and PDEs involving the local fractional derivative operators. Some typical examples for the PDEs in mathematical physics are also discussed.

This paper is devoted to study the existence and stability of mild solutions for semilinear fractional evolution equations with a nonlocal final condition. The analysis is based on analytic semigroup theory, Krasnoselskii fixed point theorem, and a special probability density function. An application to a time fractional diffusion equation with nonlocal final condition is also given.

In this study, we consider the final boundary value problem for a thermoelastic Cosserat material. With the help of a simple translation, our final problem is transformed in a usual mixed problem with boundary relations and initial data. For this new problem, we obtain some theorems of uniqueness of solutions. For this, we do not use any law of conservation of energy, as is usually done to obtain a result of uniqueness. Moreover, we do not need assumptions to ensure the boundedness of the tensors which characterize thermoelastic coefficients.

An initial–boundary value problem for Maxwell’s equations in the quasi-stationary magnetic approximation is investigated. Special gauge conditions are presented that make it possible to state the problem of independently determining the vector magnetic potential. The well-posedness of the problem is proved under general conditions on the coefficients. For quasi-stationary Maxwell equations, final observation problems formulated in terms of the vector magnetic potential are considered. They are treated as convex programming problems in a Hilbert space with an operator equality constraint. Stable sequential Lagrange principles are stated in the form of theorems on the existence of a minimizing approximate solution of the optimization problems under consideration. The possibility of applying algorithms of dual regularization and iterative dual regularization with a stopping rule is justified in the case of a finite observation error.

The role of threats is studied in cooperative normal form games. A threats-game is constructed, in which every set of players selects a joint threat strategy and then a settlement function determines the final outcome. Threat equilibria and cooperative solutions are defined for any settlement function. Two axioms are introduced which determine a unique settlement function for games with transferable utility. This settlement function is closely related to the Shapley value, and has attractive Pareto-optimality and individual-rationality properties. A simple oligopoly problem is studied to illustrate these ideas.

The weak sequential compactness of reflexive Banach spaces is used to explain the fact that certain ill-posed, linear problems become well-posed if the solutions are required to satisfy a prescribed bound. Applications are made to the computability of solutions of ill-posed problems associated with elliptic and parabolic partial differential equations.