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Recently, several authors have studied the problem of trajectory redesign for hypersonic aircraft. The usual procedure for solving such problems is to set it up as a constrained optimal control problem. Lu and Schierman used direct methods to numerically solve the optimal control problems. Alternatively, one could use Pontryagin's Minimum Principle to obtain first-order necessary conditions for the optimal control problem and obtain a two-point boundary-value problem (TPBVP). Originally created to solve two-point boundary value problems (TPBVPs), the Modified Simple Shooting Method (MSSM) has been shown to be superior, both in speed and accuracy, to known methods for solving TPBVPs. Since optimal control problems can be formulated with differential equations and boundary conditions, it seems feasible to propose that the MSSM could be used to solve problems in optimal control. Here, the original MSSM algorithm was altered and used in conjunction with Pontryagin's Minimum Principle in an attempt to solve an optimal control problem in trajectory generation. In this paper, the authors consider the problem of trajectory redesign of the unpowered reentry phase for a hypersonic air vehicle. They consider outer loop equations governing the motion of the center of mass and consider the angle of attack to be the input variable. The lift and drag forces for the aircraft considered were obtained from a polynomial neural network approximation of experimental data. Effector deflections were chosen so that the aircraft Underwent trimmed flight. (6 figures, 7 refs.).
The book is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES 2017). The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry have presented their original work and ideas, information, techniques and applications in the field of communication, computing and power technologies.
The book focuses on symplectic pseudospectral methods for nonlinear optimal control problems and their applications. Both the fundamental principles and engineering practice are addressed. Symplectic pseudospectral methods for nonlinear optimal control problems with complicated factors (i.e., inequality constraints, state-delay, unspecific terminal time, etc.) are solved under the framework of indirect methods. The methods developed here offer a high degree of computational efficiency and accuracy when compared with popular direct pseudospectral methods. The methods are applied to solve optimal control problems arising in various engineering fields, particularly in path planning problems for autonomous vehicles. Given its scope, the book will benefit researchers, engineers and graduate students in the fields of automatic control, path planning, ordinary differential equations, etc.
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This comprehensive collection of lectures by leading experts in the field introduces and reviews all relevant computer simulation methods and their applications in condensed matter systems. Volume 1 is an in-depth introduction to a vast spectrum of computational techniques for statistical mechanical systems of condensed matter. Volume 2 is a collection of state-of-the-art surveys on numerical experiments carried out for a great number of systems.
This introductory textbook/reference addresses the fundamental and mostly applied kinds of models. The focus is on models of dynamic systems that move and change over time. However, the work also proposes new methods of uncertainty treatment, offering supporting examples. Topics and features: Chapters suitable for textbook use in teaching modeling and simulation Includes sections of questions and answers, helpful in didactic work Proposes new methodology in addition to examining conventional approaches Offers some cognitive, more abstract models to give a wider insight on model building The book’s readership may consist of researchers working on multidisciplinary problems, as well educators and students. It may be used while teaching computer simulation, applied mathematics, system analysis and system dynamics.
This is a long-overdue volume dedicated to space trajectory optimization. Interest in the subject has grown, as space missions of increasing levels of sophistication, complexity, and scientific return - hardly imaginable in the 1960s - have been designed and flown. Although the basic tools of optimization theory remain an accepted canon, there has been a revolution in the manner in which they are applied and in the development of numerical optimization. This volume purposely includes a variety of both analytical and numerical approaches to trajectory optimization. The choice of authors has been guided by the editor's intention to assemble the most expert and active researchers in the various specialities presented. The authors were given considerable freedom to choose their subjects, and although this may yield a somewhat eclectic volume, it also yields chapters written with palpable enthusiasm and relevance to contemporary problems.