This book presents multi-stage feedback control designs for the system with multi-time-scale behaviour both in the continuous time domain and discrete-time domain. Multi-time-scale systems have widely separated clusters of eigenvalues, making the system matrices ill-conditioned. Due to this the direct design of a feedback controller and reduced- or full-order observers for such systems is a challenging task. Hence, the feedback controllers and observers are designed in multiple design stages, i.e. two-stage design for the two-time-scale system and three-stage design for the three-time-scale system. In this book, multi-stage feedback controller and observer designs are proposed for the three-time-scale system to reduce offline and online computational efforts. The applicability of these methods is demonstrated by simulating practical systems like a coal-fired power plant and a nuclear power plant. This book also discusses the design of multi-stage feedback controllers in discrete time. The design of state feedback control for a multi-time-scale system with a lower sampling rate fails to capture information in the fastest (very fast) and fast states. While sampling at a higher rate increases computation time. Thus, the use of single-rate sampling for such systems is unsuitable. Therefore, multi-rate state feedback controllers are designed for the multi-time-scale system, in which slow, fast, and very fast states are sampled at different sampling rates. As slow, fast and very fast states are the decoupled and internal states of the original system, these are estimated by the sequential multi-stage observers. Applications of these multirate designs to the numerical examples are demonstrated and simulations are compared with single-rate sampling methods. The methods suggested in this book result in considerable savings in online and offline computations, reduction in design complexity, and improvement in robustness and closed-loop performance. This book can be beneficial to mathematicians, scientists, researchers and practicing engineers working in this area.

This book provides a comprehensive study of multi-stage and multi-time scale design of feedback controllers for linear dynamic systems. It examines different types of controllers as can be designed for different parts of the system (subsystems) using corresponding feedback gains obtained by performing calculations (design) only with subsystem (reduced-order) matrices.The advantages of the multi-stage/multi-time scale design are presented and conditions for implementation of these controllers are established. Complete derivations and corresponding design techniques are presented for two-stage/two-time-scale, three-stage/three-time scale, and four-stage/four-time-scale systems. The techniques developed have potential applications to a large number of real physical systems. The design techniques are demonstrated on examples of mathematical models of fuel cells, especially the proton exchange membrane fuel cell.

Control and Dynamic Systems: Advances in Theory in Applications, Volume 30: Advances in Algorithms and Computational Techniques in Dynamic Systems Control, Part 3 of 3 discusses developments in algorithms and computational techniques for control and dynamic systems. This volume begins with the issue of decision making or optimal control in the natural environment. It then discusses large-scale systems composed of multiple sensors; algorithms for systems with multiplicative noise; stochastic differential games; Markovian targets; low-cost microcomputer and true digital control systems; and algorithms for the design of teleoperated systems. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.

This book introduces key concepts for systematically controlling engineering systems that possess interacting phenomena occurring at widely different speeds. The aim is to present the reader with control techniques that extend the benefits of model reduction of singular perturbation theory to a larger class of nonlinear dynamical systems. New results and relevant background are presented through insightful examples that cover a wide range of applications from different branches of engineering. This book is unique because it: presents a new perspective on existing control methods and thus broadens their application to a larger class of nonlinear dynamical systems; discusses general rather than problem-specific developments to certain applications or disciplines in order to provide control engineers with useful analytical tools ; addresses new control problems using singular perturbation methods, including closed-form results for control of nonminimum phase systems.

Classical Feedback Control with Nonlinear Multi-Loop Systems describes the design of high-performance feedback control systems, emphasizing the frequency-domain approach widely used in practical engineering. It presents design methods for high-order nonlinear single- and multi-loop controllers with efficient analog and digital implementations. Bode integrals are employed to estimate the available system performance and to determine the ideal frequency responses that maximize the disturbance rejection and feedback bandwidth. Nonlinear dynamic compensators provide global stability and improve transient responses. This book serves as a unique text for an advanced course in control system engineering, and as a valuable reference for practicing engineers competing in today’s industrial environment.

Control and Dynamic Systems: Advances in Theory and Application, Volume 27: System Identification and Adaptive Control, Part 3 of 3 deals with system parameter identification and adaptive control. It presents useful techniques for adaptive control systems. This volume begins by presenting a powerful approach to multivariable model reference adaptive control based on the ideas and techniques of disturbance-accommodating control theory. It then discusses the modeling of biological systems; optimal control for air conditioning systems; linear programming for constrained multivariable process control; finite element approximation; development of irreducible state space singular systems; and discrete systems with multiple time scales. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.

This book describes the research progress of the control design about strict-feedback nonlinear systems. A novel gain control design method is proposed, which greatly simplifies the construction procedure of controller for strict-feedback nonlinear systems. The control design problem of strict-feedback nonlinear systems is converted into the determination problem of gain parameters or the construction of dynamic gain equations. Therefore, the tedious iterative design procedure is effectively avoided. This book can be used as a reference for researchers in the field of control theory and engineers seeking advanced methods in practical control applications.