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Author: N S Manjarekar Publisher: Springer Science & Business Media ISBN: 3642275311 Category : Technology & Engineering Languages : en Pages : 96
Book Description
In this work we derive asymptotically stabilizing control laws for electrical power systems using two nonlinear control synthesis techniques. For this transient stabilization problem the actuator considered is a power electronic device, a controllable series capacitor (CSC). The power system is described using two different nonlinear models - the second order swing equation and the third order flux-decay model. To start with, the CSC is modeled by the injection model which is based on the assumption that the CSC dynamics is very fast as compared to the dynamics of the power system and hence can be approximated by an algebraic equation. Here, by neglecting the CSC dynamics, the input vector $g(x)$ in the open loop system takes a complex form - the injection model. Using this model, interconnection and damping assignment passivity-based control (IDA-PBC) methodology is demonstrated on two power systems: a single machine infinite bus (SMIB) system and a two machine system. Further, IDA-PBC is used to derive stabilizing controllers for power systems, where the CSC dynamics are included as a first order system. Next, we consider a different control methodology, immersion and invariance (I\&I), to synthesize an asymptotically stabilizing control law for the SMIB system with a CSC. The CSC is described by a first order system. As a generalization of I\&I, we incorporate the power balance algebraic constraints in the load bus to the SMIB swing equation, and extend the design philosophy to a class of differential algebraic systems. The proposed result is then demonstrated on another example: a two-machine system with two load buses and a CSC. The controller performances are validated through simulations for all cases.
Author: N S Manjarekar Publisher: Springer Science & Business Media ISBN: 3642275311 Category : Technology & Engineering Languages : en Pages : 96
Book Description
In this work we derive asymptotically stabilizing control laws for electrical power systems using two nonlinear control synthesis techniques. For this transient stabilization problem the actuator considered is a power electronic device, a controllable series capacitor (CSC). The power system is described using two different nonlinear models - the second order swing equation and the third order flux-decay model. To start with, the CSC is modeled by the injection model which is based on the assumption that the CSC dynamics is very fast as compared to the dynamics of the power system and hence can be approximated by an algebraic equation. Here, by neglecting the CSC dynamics, the input vector $g(x)$ in the open loop system takes a complex form - the injection model. Using this model, interconnection and damping assignment passivity-based control (IDA-PBC) methodology is demonstrated on two power systems: a single machine infinite bus (SMIB) system and a two machine system. Further, IDA-PBC is used to derive stabilizing controllers for power systems, where the CSC dynamics are included as a first order system. Next, we consider a different control methodology, immersion and invariance (I\&I), to synthesize an asymptotically stabilizing control law for the SMIB system with a CSC. The CSC is described by a first order system. As a generalization of I\&I, we incorporate the power balance algebraic constraints in the load bus to the SMIB swing equation, and extend the design philosophy to a class of differential algebraic systems. The proposed result is then demonstrated on another example: a two-machine system with two load buses and a CSC. The controller performances are validated through simulations for all cases.
Author: Declan Bates Publisher: Springer ISBN: 3540737197 Category : Technology & Engineering Languages : en Pages : 358
Book Description
This is the first book to focus on the use of nonlinear analysis and synthesis techniques for aircraft control. It is also the first book to address in detail closed-loop control problems for aircraft "on-ground" – i.e. speed and directional control of aircraft before take-off and after touch down. The book will be of interest to engineers, researchers, and students in control engineering, and especially aircraft control.
Author: Ülle Kotta Publisher: Springer ISBN: 3540393765 Category : Technology & Engineering Languages : en Pages : 159
Book Description
The purpose of this book is twofold: To survey control system design methods based on the system inversion technique and to collect into one place the many recent results in the field. It has been known for some time that inverse systems may be used to solve numerous control problems. Despite the importance and conceptual simplicity of this topic there appears to be no monograph written on it. The purpose of this work is therefore to present and apply a systematic design method which bases itself on the fundamental system property of invertibility. Many different theoretical and practical aspects are considered in this volume working from elementary topics in the first section to current research in the second.
Author: Luca Zaccarian Publisher: Princeton University Press ISBN: 1400839025 Category : Mathematics Languages : en Pages : 303
Book Description
This book provides a wide variety of state-space--based numerical algorithms for the synthesis of feedback algorithms for linear systems with input saturation. Specifically, it addresses and solves the anti-windup problem, presenting the objectives and terminology of the problem, the mathematical tools behind anti-windup algorithms, and more than twenty algorithms for anti-windup synthesis, illustrated with examples. Luca Zaccarian and Andrew Teel's modern method--combining a state-space approach with algorithms generated by solving linear matrix inequalities--treats MIMO and SISO systems with equal ease. The book, aimed at control engineers as well as graduate students, ranges from very simple anti-windup construction to sophisticated anti-windup algorithms for nonlinear systems. Describes the fundamental objectives and principles behind anti-windup synthesis for control systems with actuator saturation Takes a modern, state-space approach to synthesis that applies to both SISO and MIMO systems Presents algorithms as linear matrix inequalities that can be readily solved with widely available software Explains mathematical concepts that motivate synthesis algorithms Uses nonlinear performance curves to quantify performance relative to disturbances of varying magnitudes Includes anti-windup algorithms for a class of Euler-Lagrange nonlinear systems Traces the history of anti-windup research through an extensive annotated bibliography
Author: C.I. Byrnes Publisher: Springer Science & Business Media ISBN: 1475721358 Category : Science Languages : en Pages : 315
Book Description
In its broadest sense, nonlinear synthesis involves in fact the synthesis of sometimes so phisticated or complex control strategies with the aim of prescribing, or at least influencing, the evolution of complex nonlinear systems. Nonlinear synthesis requires the development of methodologies for modeling complex systems, for the analysis of nonlinear models, and for the systematic design of control schemes or feedback laws which can achieve a wide variety of prescribed objectives. The modeling, analysis and control of complex systems in the face of uncertainty form on of the major components of the current research program in the Department of Systems and Decision Sciences (SDS) at the International Institute for Applied Systems Analysis (IIASA). In June 1989, a IIASA workshop on Nonlinear Synthesis, sponsored by SDS, was held in Sopron, Hungary. We are proud to present this volume as the proceedings of this workshop, a workshop attened by prominent researchers in nonlinear systems from both the East and the West. Since the promotion and encouragement of scientific cooperation between researchers in the East and in the West is one of the goals at IIASA, we feel the Sopron Conference on Nonlinear Synthesis was very successful. Moreover, we were especially pleased by the impressive new advances presented at the workshop which, in this volume, are now part of the conference record.
Author: Marcelo G. S. Bruno Publisher: Morgan & Claypool Publishers ISBN: 1627051198 Category : Computers Languages : en Pages : 101
Book Description
In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable. We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move to the general nonlinear, non-Gaussian stochastic filtering problem and present particle filtering as a sequential Monte Carlo approach to solve that problem in a statistically optimal way. We review several techniques to improve the performance of particle filters, including importance function optimization, particle resampling, Markov Chain Monte Carlo move steps, auxiliary particle filtering, and regularized particle filtering. We also discuss Rao-Blackwellized particle filtering as a technique that is particularly well-suited for many relevant applications such as fault detection and inertial navigation. Finally, we conclude the notes with a discussion on the emerging topic of distributed particle filtering using multiple processors located at remote nodes in a sensor network. Throughout the notes, we often assume a more general framework than in most introductory textbooks by allowing either the observation model or the hidden state dynamic model to include unknown parameters. In a fully Bayesian fashion, we treat those unknown parameters also as random variables. Using suitable dynamic conjugate priors, that approach can be applied then to perform joint state and parameter estimation.
Author: N S Manjarekar
Author: N S Manjarekar
Author: Declan Bates
Author: Christopher I. Byrnes
Author: C. I. Byrnes
Author: Ming-Lei Liou
Author: Ülle Kotta
Author: Luca Zaccarian
Author: C.I. Byrnes
Author: Harry L. Van Trees
Author: Marcelo G. S. Bruno