Multi Stage Feedback Control Design For Multi Time Scale System


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Multi-stage Feedback Control Design for Multi-time-scale System


Multi-stage Feedback Control Design for Multi-time-scale System

Author: Ravindra Munje

language: en

Publisher: Springer Nature

Release Date: 2024-08-23


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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.

Multi-Stage and Multi-Time Scale Feedback Control of Linear Systems with Applications to Fuel Cells


Multi-Stage and Multi-Time Scale Feedback Control of Linear Systems with Applications to Fuel Cells

Author: Verica Radisavljević-Gajić

language: en

Publisher: Springer

Release Date: 2019-02-12


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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 V30: Advances in Algorithms and Computational Techniques in Dynamic System Control Part 3 of 3


Control and Dynamic Systems V30: Advances in Algorithms and Computational Techniques in Dynamic System Control Part 3 of 3

Author: C.T. Leonides

language: en

Publisher: Elsevier

Release Date: 2012-12-02


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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.