Control and Dynamic Systems: Advances in Theory and Applications, Volume 54: System Performance Improvement and Optimization Techniques and their Applications in Aerospace Systems covers the issue of aerospace system performance and optimization techniques in aerospace systems. This book is composed of 12 chapters and begins with an examination of the techniques for aircraft conceptual design for mission performance. The succeeding chapters describe the balances and optimized design for aircraft and spacecraft structures through finite element procedures and the application of the knowledge-based system techniques for pilot aiding. These topics are followed by discussions of the optimal sensor placement for on-orbit modal identification experiments; the optimization techniques for helicopter airframe vibrations design; the size reduction techniques for efficient aeroservoelastic model determination; sensitivity analysis of eigendata of aeroelastic systems; and a simplified solution for transient structural dynamic problems with local nonlinearities. Other chapters explore a reduction algorithm for systems with integrators and the techniques for overcoming the difficulty of nonuniqueness of mode shape in modal analysis when random input data are not or cannot be measured. The last chapters consider the combined concepts of Krylov vectors and parameter matching and their application to develop model-reduction algorithms for structural dynamics. These chapters also provide the techniques for the development of new tracking algorithms that would incorporate explicit models of the maneuvering/nonmaneuvering phases of target encounter. This book will prove useful to aerospace, control, systems, and design engineers.

Designed Experiments for Science and Engineering is a versatile and overarching toolkit that explores various methods of designing experiments for over 20 disciplines in science and engineering. Designed experiments provide a structured approach to hypothesis testing, data analysis, and decision‐making. They allow researchers and engineers to efficiently explore multiple factors, interactions, and their impact on outcomes, ultimately leading to better‐designed processes, products, and systems across a wide range of scientific and engineering disciplines. Each discipline covered in this book includes the key characteristics of the steps in choosing and executing the experimental designs (one factor, fractional factorial, mixture experimentation, factor central composite, 3‐factor + central composite, etc.) and reviews the various statistical tools used as well as the steps in how to utilize each (standard deviation analysis, analysis of variance [ANOVA], relative standard deviation, bias analysis, etc.). This book is essential reading for students and professionals who are involved in research and development within various fields in science and engineering, such as mechanical engineering, environmental science, manufacturing, and aerospace engineering.