Control Theory in Engineering

The subject matter of this book ranges from new control design methods to control theory applications in electrical and mechanical engineering and computers. The book covers certain aspects of control theory, including new methodologies, techniques, and applications. It promotes control theory in practical applications of these engineering domains and shows the way to disseminate researchers’ contributions in the field. This project presents applications that improve the properties and performance of control systems in analysis and design using a higher technical level of scientific attainment. The authors have included worked examples and case studies resulting from their research in the field. Readers will benefit from new solutions and answers to questions related to the emerging realm of control theory in engineering applications and its implementation

Heart motion prediction based on adaptive estimation aşgorithms fo robotic-assisted beating heart surgery

Ankara : The Department of Electrical and Electronics Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.Thesis (Master's) -- Bilkent University, 2011.Includes bibliographical references leaves 90-93.Robotic assisted beating heart surgery aims to allow surgeons to operate on a beating heart without stabilizers as if the heart is stationary. The robot actively cancels heart motion by closely following a point of interest (POI) on the heart surface—a process called Active Relative Motion Canceling (ARMC). Due to the high bandwidth of the POI motion, it is necessary to supply the controller with an estimate of the immediate future of the POI motion over a prediction horizon in order to achieve sufficient tracking accuracy. In this thesis two prediction algorithms, using an adaptive filter to generate future position estimates, are studied. In addition, the variation in heart rate on tracking performance is studied and the prediction algorithms are evaluated using a 3 degrees of freedom test-bed with prerecorded heart motion data. Besides this, a probabilistic robotics approach is followed to model and characterize noise of the sensor system that collects heart motion data used in this study. The generated model is employed to filter and clean the noisy measurements collected from the sensor system. Then, the filtered sensor data is used to localize POI on the heart surface accurately. Finally, estimates obtained from the adaptive prediction algorithms are integrated to the generated measurement model with the aim of improving the performance of the presented approach.Tuna, Eser ErdemM.S

Measurements, Models, Systems and Design

531 s.

Model reference adaptive control system using frequency domain performance specifications

MRAS (Model Reference Adaptive System) to achieve frequency domain performance specifications with different transfer function identification techniques are experimentally studied. Standard open loop and closed loop recursive least squares (RLS) system identification techniques are implemented along with methods based on bandpass filters and steady-state Kalman filter. The behavior of the MRAS when combined with the different system identification techniques is discussed. Based on experimental work performed on MRAS using open loop system identification, it was found that the system can achieve performance specifications in all process conditions. It was noticed that the DC bias changes in process input when process changes, delays the convergence of the system identification in open loop system identification. Closed loop system identification was found inadequate for use in MRAS. The system identification based on bandpass filter approach was found slow in convergence and so inefficient for use in MRAS. The use of Kalman filter for system identification resulted in noisy gains on adaptive PI controller. Based on the results obtained, it is concluded that MRAS to achieve frequency domain performance specifications is practical and capable of being used in industrial process control when coupled with open loop identification based on frequency domain concepts. The proposed approach provides a better method for maintaining performance robustness while guaranteeing stability margins in adaptive control than that obtained from time domain adaptive control

Modeling and control of thermoacoustic instabilities

This work deals with modeling and control of thermoacoustic combustion instabilities in lean premixed combustion systems. Because of the complex interactions present in thermoacoustic systems, a network modeling approach is used. The model of each network element or subsystem is obtained analytically, numerically, or by making use of experimental techniques. The dynamics of a network system are determined experimentally by making use of a transfer matrix measurement technique. The transfer functions of a premixed flame have been determined experimentally on an atmospheric combustion test facility with a full-scale gas turbine burner, for a wide variety of operating conditions. An analytical model of the dynamic behavior of the reaction zone was made. In this model, the heat release fluctuations are assumed to be caused by fluctuations of the mass fraction of fuel and by fluctuations in the burning velocity. The model proved to be in good agreement with experimental results. Wave propagation in complex three-dimensional geometries is modeled by making use of a modal expansion technique. The modes used for the modal expansion can be obtained analytically for relatively simple geometries, or numerically (finite element method) for geometries of any complexity. By representing the modal expansion in state-space, a very numerically efficient and robust model is obtained. The thermoacoustic network model combines the state-space representations of the sub-systems in one system. The system can be analyzed in the time domain or in the frequency domain. The stability analysis is straightforward and does not require a numerical search. Non linear elements can easily be incorporated in the time domain simulation. This novel method has been validated by comparison with analytic solutions of simple thermoacoustic systems found in literature, by comparison with Finite Element codes, and by comparison with experimental results. An excellent agreement was found for all comparisons. When including non-linear elements in an annular system, a rotating acoustic field is predicted, which corresponds to experimental observations. This result has been verified analytically. Based on network models, a model based controller has been obtained using H∞ optimization. This controller has been tested in simulation and experiment on a single burner rig and proved to suppress acoustic levels by more than 25dB. An adaptive controller, based on a genetic algorithm, has been developed that does not require any knowledge about the system. This controller has been tested and proved to have similar performance as the model-based controllers. An active control system for multi-burner configurations has been developed and proved to perform well in simulations

Proceedings of the Workshop on Applications of Distributed System Theory to the Control of Large Space Structures

Two general themes in the control of large space structures are addressed: control theory for distributed parameter systems and distributed control for systems requiring spatially-distributed multipoint sensing and actuation. Topics include modeling and control, stabilization, and estimation and identification

Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, part 1

The proceedings of the workshop are presented. Some areas of discussion are as follows: modeling, systems identification, and control of flexible aircraft, spacecraft, and robotic systems

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area