This thesis presents the formulation and solution of a new problem in systems and control theory, called the Network Realization Problem. Its relationship to other problems, such as State Realization and Structural Identifiability, is shown. The motivation for this work is the desire to completely quantify the conditions for transitioning between different mathematical representations of linear time-invariant systems. The solution to this problem is useful for theorists because it lays a foundation for quantifying the information cost of identifying a system's complete network structure from the transfer function.

In the study of linear time-invariant systems, a number of definitions, such as controllability, observability, not having decentralized fixed modes, minimum phase, etc., have been made. These definitions are highly useful in obtaining existence results for solving various types of control problems, but a drawback to these definitions is that they are binary, which simply determines whether a system is, for instance, either controllable or uncontrollable. In practical situations, however, there are many uncertainties in a system’s parameters caused by linearization, modelling errors, discretizations, and other numerical approximations and/or errors. So knowing that a system is controllable can sometimes be misleading if the controllable system is actually "almost" uncontrollable as a result of such uncertainties. Since an "almost" uncontrollable system poses significant difficulty in designing a quality controller, a continuous measure of controllability, called a controllability radius, is more desirable to use and has been widely studied in the past. The main focus of this thesis is to extend the development behind the controllability radius, with an emphasis on real parametric perturbations, to other definitions, replacing the traditional binary 'yes/no' metrics with continuous measures. We study four topics related to this development. First, we generalize the concept of real perturbation values of a matrix to the cases of matrix pairs and matrix triplets. By doing so, we are able to deal with more general perturbation structures and subsequently study, in addition to standard LTI systems, other types of systems such as LTI descriptor and time-delay systems. Second, we introduce the real decentralized fixed mode (DFM) radius, the real transmission zero at s radius, and the real minimum phase radius, which respectively measure how "close" i) a decentralized LTI system is to having a DFM, ii) a centralized system is to having a transmission zero at a particular point s in the complex plane, and iii) a minimum phase system is to being a nonminimum phase system. These radii are defined in terms of real parametric perturbations, and computable formulas for these radii are derived using a characterization based on real perturbation values and the aforementioned generalizations. Third, we present two efficient algorithms to i) solve the general real perturbation value problem, and ii) evaluate the various real LTI robustness radii introduced in this thesis. Finally as the last topic, we study the ability of a LTI system to achieve high performance control, and characterize the difficulty of achieving high performance control using a new continuous measure called the Toughness Index. A number of examples involving the various measures are studied in this thesis.

In the study of linear time-invariant systems, a number of definitions, such as controllability, observability, not having decentralized fixed modes, minimum phase, etc., have been made. These definitions are highly useful in obtaining existence results for solving various types of control problems, but a drawback to these definitions is that they are binary, which simply determines whether a system is, for instance, either controllable or uncontrollable. In practical situations, however, there are many uncertainties in a system’s parameters caused by linearization, modelling errors, discretizations, and other numerical approximations and/or errors. So knowing that a system is controllable can sometimes be misleading if the controllable system is actually "almost" uncontrollable as a result of such uncertainties. Since an "almost" uncontrollable system poses significant difficulty in designing a quality controller, a continuous measure of controllability, called a controllability radius, is more desirable to use and has been widely studied in the past. The main focus of this thesis is to extend the development behind the controllability radius, with an emphasis on real parametric perturbations, to other definitions, replacing the traditional binary 'yes/no' metrics with continuous measures. We study four topics related to this development. First, we generalize the concept of real perturbation values of a matrix to the cases of matrix pairs and matrix triplets. By doing so, we are able to deal with more general perturbation structures and subsequently study, in addition to standard LTI systems, other types of systems such as LTI descriptor and time-delay systems. Second, we introduce the real decentralized fixed mode (DFM) radius, the real transmission zero at s radius, and the real minimum phase radius, which respectively measure how "close" i) a decentralized LTI system is to having a DFM, ii) a centralized system is to having a transmission zero at a particular point s in the complex plane, and iii) a minimum phase system is to being a nonminimum phase system. These radii are defined in terms of real parametric perturbations, and computable formulas for these radii are derived using a characterization based on real perturbation values and the aforementioned generalizations. Third, we present two efficient algorithms to i) solve the general real perturbation value problem, and ii) evaluate the various real LTI robustness radii introduced in this thesis. Finally as the last topic, we study the ability of a LTI system to achieve high performance control, and characterize the difficulty of achieving high performance control using a new continuous measure called the Toughness Index. A number of examples involving the various measures are studied in this thesis.

In this paper, the gap metric is introduced to study the robustness of the stability of feedback systems. A relation between the gap metric and coprime fractions is also investigated. It is shown that the stability radius of the controller in the gap metric is equal to the stability margin of the controller. In the loop-shaping design procedure in the £h-gap metric, it is practically hard to formulate an ideal controller. Finally, this paper studied the conservatism of the gap metric, and proposed some properties that can help for control design and analysis.

The Best MPhil Thesis in the Faculties of Dentistry, Engineering, Medicine and Science (University of Hong Kong), Li Ka Shing Prize,2009-2010 / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

This thesis studies the indirect adaptive control for discrete linear time invariant systems. The adaptive control strategy is based on the linear quadratic regulator that places the closed loop poles such that an infinite stage quadratic cost function is minimized. The plant parameters are identified recursively using a projection algorithm. / First, we study the effect of the model over-parametrization. For this purpose, we introduce an algorithm to generate the controller parameters recursively. This asymptotic reformulation is shown to overcome situations in which the pole-zero cancellation is a limit point of the identification algorithm. We also show that the algorithm will generate a unique control sequence that converges asymptotically to the solution of the Diophantine (pole assignment) equation. / Next, we study the stability of the proposed adaptive scheme in both deterministic and stochastic cases. We show that the global stability of the resulting adaptive scheme is obtained with no implicit assumptions about parameter convergence or the nature of the external input. Then the global convergence of the adaptive algorithm is obtained if the external input is "persistently exciting". By convergence we mean that the adaptive control will converge to the optimal control of the system. / The performance of the adaptive algorithm in the presence of deterministic disturbances is also considered, where we show that the adaptive controller performs relatively well if the model order is high enough to include a description of the disturbances.

Thesis (Ph.D.)--University of Western Australia, 2007.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 102-108). Available also in a digital version from Dissertation Abstracts.

by Michael Athans. / Bibliography: leaf [3]. / "August 1983." / Supported by the Office of Naval Research under Grant ONR/N00014-82-K-0582 NR 606-003 NASA Ames and Langley Research Centers under Grant NGL-22-009-124

CAPES / O objetivo desta dissertação é propor uma técnica para a síntese via realimentação de estados para sistemas lineares e invariantes no tempo, considerando que os estados realimentados são previamente quantizados. Para tanto, o erro de quantização é inicialmente modelado como um ruído externo. Assim, o problema de obter os ganhos de realimentação de estados, se torna um problema de projetar os ganhos que minimizem a norma H¥ do sistema controlado. Os ganhos de realimentação são calculados pela solução de um conjunto de condições descritas na forma de desigualdades matriciais lineares. A técnica é ilustrada pela aplicação da realimentação de estados quantizada em um servomecanismo. / The main objective of this dissertation is to propose a technique for synthesis by statefeedback for linear time-invariant systems, considering that the states are quantized before the feedback. To tackle such problem, the quantization error is initially modeled as an external noise. Therefore, the problem of getting the state-feedback gains, becomes a problem of designing the gains that minimize the H¥ norm of the system. The state-feedback gains are calculated by solving a set of conditions described in the form of linear matrix inequalities. The technique is illustrated by applying the of feedback of quantized states to a servo-mechanism.