Control And Dynamic Systems V57 Multidisciplinary Engineering Systems Design And Optimization Techniques And Their Application

Control and Dynamic Systems: Advances in Theory and Applications, Volume 57: Multidisciplinary Engineering Systems: Design and Optimization Techniques and their Application deals with techniques used in the design and optimization of future engineering systems. Comprised of 11 chapters, this book covers techniques for improving product design quality in multidisciplinary systems. These techniques include decomposition techniques for synthesis process; optimization for aircraft systems; actuator and sensor placement; and robust techniques in system design and control process. Students, research workers, and practising engineers will find this book invaluable.

In this publication all the recent advances in the field of modern control theory are covered and presented. This volume covers various topics, including decomposition methods for multidisciplinary synthesis and multilevel optimization techniques for aircraft.

Control and Dynamic Systems: Advances in Theory and Applications reviews progress in the field of control and dynamic systems theory and applications. Topics include multistage models and fitting them to input/output data; computer-aided control systems design techniques; multilevel optimization of multiple arc trajectories; and nonlinear smoothing techniques. Solutions of dynamic games are also considered, and a survey of Soviet contributions to control theory is presented. Comprised of six chapters, this volume begins with a discussion on a number of important issues with respect to the modeling of a dynamic system, the beginning point for the resolution of the system synthesis problem. Issues with respect to the utilization of the Kalman filter as a concise model for the identification of a large class of dynamic systems are explored, along with computational and convergence issues. The application of computer-aided design techniques to control engineering problems is the subject of the next chapter. The book also evaluates multilevel systems optimization techniques and their application to a rather complex systems problem before concluding with an overview of the evolutionary growth of Soviet contributions to control theory. This monograph will be useful to mathematicians and engineers.

Control and Dynamic Systems, Volume 37: Advances in Industrial Systems provides an overview of the state of knowledge in industrial systems. This volume contains nine chapters and begins with a paper on the objective measures used to characterize the performance of computers which control critical processes. This is followed by separate chapters on the design of automotive power train control systems; control techniques in the pulp and paper industry; developments production scheduling research and practice; a general model-based failure detection and diagnosis methodology; and the application of model-predictive control techniques to problems with several input and output variables. Subsequent chapters deal with techniques for dealing with the problem of providing a complete, coherent, and reliable data base from a collection of switch and breaker status data and measurements; systematic approaches to modifying a finite element model; and optimization techniques in industrial chemical systems. The contributions in this volume will provide a unique and significant reference source for practicing professionals as well as those involved with advancing the state of the art.

Control and Dynamic Systems: Advances in Theory and Applications, Volume 56: Digital and Numeric Techniques and their Applications in Control Systems, Part 2 of 2 covers the significant developments in digital and numerical techniques for the analysis and design of modern complex control systems. This volume is composed of 12 chapters and starts with a description of the design techniques of linear constrained discrete-time control systems. The subsequent chapters describe the techniques dealing with robust real-time system identification, the adaptive control algorithms, and the utilization of methods from generalized interpolation and operator theory to deal with a wide range of problems in robust control. These topics are followed by reviews f the decentralized control design for interconnected uncertain systems; the computation of frequency response of descriptor systems by rational interpolation; the techniques for the synthesis of multivariable feedback control laws; and the effect of the initial condition in state estimation for discrete-time linear systems. Other chapters illustrate practical, efficient, and reliable numerical algorithms for robust multivariable control design of linear time-invariant systems, as well as a complete analysis of closed-loop transfer recovery in discrete-time systems using observer-based controllers. The last chapters provide the techniques in robust policy-making in the global economic environment and the implications of robust control techniques for continuous-time systems. This book will prove useful to process, control, systems, and design engineers.

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.

Control and Dynamic Systems, Volume 58: Computer-Aided Design/Engineering (CAD/CAE) Techniques and Their Applications Part 1 of 2 is the first of a two-volume sequence that manifests the significance and the power of CAD/CAE techniques that are available and their further development for the essential role they play in the design of modern engineering systems. The volume contains eight chapters and begins with a study on the reliability and control (limiting) of errors in the CAD/CAE design process. This is followed by separate chapters on methods for organizing engineering design and design techniques in a CAD/CAE database system; the various high-level tools to support a CAD engineer working in the graphical user interface computer environment; and finite element analysis techniques in the CAD/CAE process. Subsequent chapters deal with explicit and implicit aspects of large-scale nonlinear finite element analysis; techniques in parallel computing architectures; and a comprehensive treatment of (iterative) change in the design process. This volume will provide a significant and, perhaps, unique reference source for students, research workers, practicing engineers, and others on the international scene for many years.

Control system engineering is the branch of engineering which deals with the principles of control theory to design a system which gives desired behaviour in a controlled manner. Hence, this is interdisciplinary. Control system engineers analyse, design and optimize complex systems which consist of highly integrated coordination of mechanical, electrical, chemical, metallurgical, electronic or pneumatic elements. Thus control engineering deals with diverse range of dynamic systems which include human and technological interfacing. The applications of automatic control system is believed to be in use even from the ancient civilizations. Several types of water clock were designed and implemented to measure the time accurately from the third century BC, by Greeks and Arabs. The two methods of control systems include classical methods and modern methods. The mathematical model system is set up as first step followed by analysis designing and testing. Necessary conditions for the stability are checked and finally optimization follows. In classical method, mathematical modelling is usually done in time domain, frequency domain or complex s domain. Modern control engineering deals with Multiple Input Multiple Output (MIMO) systems, State space approach, Eigen values and vectors etc. Instead of transforming complex ordinary differential equations, modern approach converts higher order equations to first order differential equations and solved by vector methods. Control System Engineering focuses on analysis and design of systems to improve the speed of response, accuracy and stability of system. It seeks to understand physical systems, using mathematical modelling, in terms of inputs, outputs and various components with different behaviours; use control systems design tolls to develop controllers for those systems; and implement controllers in physical systems employing available technology.