Sampling from a system-theoretic viewpoint

This paper studies a system-theoretic approach to the problem of reconstructing an analog signal from its samples. The idea, borrowed from earlier treatments in the control literature, is to address the problem as a hybrid model-matching problem in which performance is measured by system norms. \ud \ud The paper is split into three parts. In Part I we present the paradigm and revise the lifting technique, which is our main technical tool. In Part II optimal samplers and holds are designed for various analog signal reconstruction problems. In some cases one component is fixed while the remaining are designed, in other cases all three components are designed simultaneously. No causality requirements are imposed in Part II, which allows to use frequency domain arguments, in particular the lifted frequency response as introduced in Part I. In Part III the main emphasis is placed on a systematic incorporation of causality constraints into the optimal design of reconstructors. We consider reconstruction problems, in which the sampling (acquisition) device is given and the performance is measured by the $L^2$-norm of the reconstruction error. The problem is solved under the constraint that the optimal reconstructor is $l$-causal for a given $l\geq 0,$ i.e., that its impulse response is zero in the time interval $(-\infty,-l h),$ where $h$ is the sampling period. We derive a closed-form state-space solution of the problem, which is based on the spectral factorization of a rational transfer function

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Magnetic Actuators and Suspension for Space Vibration Control

The research on microgravity vibration isolation performed at the University of Virginia is summarized. This research on microgravity vibration isolation was focused in three areas: (1) the development of new actuators for use in microgravity isolation; (2) the design of controllers for multiple-degree-of-freedom active isolation; and (3) the construction of a single-degree-of-freedom test rig with umbilicals. Described are the design and testing of a large stroke linear actuator; the conceptual design and analysis of a redundant coarse-fine six-degree-of-freedom actuator; an investigation of the control issues of active microgravity isolation; a methodology for the design of multiple-degree-of-freedom isolation control systems using modern control theory; and the design and testing of a single-degree-of-freedom test rig with umbilicals

Doctor of Philosophy

dissertationThe dissertation is concerned with the development and analysis of adaptive algorithms for the rejection of unknown periodic disturbances acting on an unknown system. The rejection of periodic disturbances is a problem frequently encountered in control engineering, and in active noise and vibration control in particular. A new adaptive algorithm is presented for situations where the plant is unknown and may be time-varying. Known as the adaptive harmonic steady-state or ADHSS algorithm, the approach consists in obtaining on-line estimates of the plant frequency response and of the disturbance parameters. The estimates are used to continuously update control parameters and cancel or minimize the effect of the disturbance. The dynamic behavior of the algorithm is analyzed using averaging theory. Averaging theory allows the nonlinear time-varying closed-loop system to be approximated by a nonlinear time-invariant system. Extensions of the algorithm to systems with multiple inputs/outputs and disturbances consisting of multiple frequency components are provided. After considering the rejection of sinusoidal disturbances of known frequency, the rejection of disturbances of unknown frequency acting on an unknown and time-varying plant is considered. This involves the addition of frequency estimation to the ADHSS algorithm. It is shown that when magnitude phase-locked loop (MPLL) frequency estimation is integrated with the ADHSS algorithm, the two components work together in such a way that the control input does not prevent frequency tracking by the frequency estimator and so that the order of the ADHSS can be reduced. While MPLL frequency estimation can be combined favorably with ADHSS disturbance rejection, stability is limited due to the local convergence properties of the MPLL. Thus, a new frequency estimation algorithm with semiglobal stability properties is introduced. Based on the theory of asynchronous electric machines, the induction motor frequency estimator, or IMFE, is shown to be appropriate for disturbance cancellation and, with modification, is shown to increase stability of the combined ADHSS/MPLL algorithm. Extensive active noise control experiments demonstrate the performance of the algorithms presented in the dissertation when disturbance and plant parameters are changing