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Thesis (MS)?Naval Postgraduate School, 1967

Thesis (MS)--U.S. Naval Postgraduate School, 1961

In this paper, the problem of optimal power allocation in Cognitive Radio (CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on providing limited feedback solutions aiming at maximizing the secondary system rate subject to a constraint on the average interference caused to primary communication. The limited feedback solutions are obtained by reducing the information available at secondary transmitter (STx) for the link between STx and the secondary receiver (SRx) as well as by limiting the level of available information at STx that corresponds to the link between the STx and the primary receiver PRx. Monte Carlo simulation results are given that allow to quanitfy the performance achieved by the proposed algorithms.

A two-phase study was performed using the USAF NT-33A variable stability airplane. In Phase I of the study the effect of the evaluation technique used in the assessment of airplane flying qualities for the air combat flight phase was investigated. In-flight evaluations with and without a target airplane were performed for selected configurations from AFFDL-TR-70-74. The results from the evaluations with a target airplane were compared to results obtained with a target airplane and to the results in AFFDL-TR-70-74. In all cases, the evaluations performed without a target airplane were adequate to reveal potential flying qualities problems in the detailed pilot comments. There was, however, larger variability in the rating differences between the evaluations performed with and without a target. There were also significant rating differences between the evaluations performed with and without a target for about 15% of the configurations.

Feedback management in an individually-paced instruction system can be mathematically analyzed by the use of computer simulation models. Because of the student "down time" or waiting time associated with individualized instruction situations, reinforcement activities have been reduced to less than ideal levels. By proper time management the student is insured of making at least average continuous progress through the curriculum while receiving an acceptable level of reinforcement through the successful completion of tasks. This theoretical study used DYNAMO II programing on an IBM 360 computer to run several simulation models. In each case the pacing variable was found to be of primary importance to the success of the overall instructional system. (MC)

This paper describes loop shaping control design in feedback control systems, primarily from a practical stand point that considers design specifications. Classical feedback control design theory, for linear systems where the plant transfer function is known, has been around for a long time. But it s still a challenge of how to translate the theory into practical and methodical design techniques that simultaneously satisfy a variety of performance requirements such as transient response, stability, and disturbance attenuation while taking into account the capabilities of the plant and its actuation system. This paper briefly addresses some relevant theory, first in layman s terms, so that it becomes easily understood and then it embarks into a practical and systematic design approach incorporating loop shaping design coupled with lead-lag control compensation design. The emphasis is in generating simple but rather powerful design techniques that will allow even designers with a layman s knowledge in controls to develop effective feedback control designs.

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

The closely-related problems of designing reliable feedback stabilization strategy and coordinating decentralized feedbacks are considered. Two approaches are taken. A geometric characterization of the structure of control interaction (and its dual) was first attempted and a concept of structural homomorphism developed based on the idea of 'similarity' of interaction pattern. The idea of finding classes of individual feedback maps that do not 'interfere' with the stabilizing action of each other was developed by identifying the structural properties of nondestabilizing and LQ-optimal feedback maps. Some known stability properties of LQ-feedback were generalized and some partial solutions were provided to the reliable stabilization and decentralized feedback coordination problems. A concept of coordination parametrization was introduced, and a scheme for classifying different modes of decentralization (information, control law computation, on-line control implementation) in control systems was developed.

Response lags are generic to almost any physical system and often play a crucial role in the feedback loops present in artificial nanodevices and biological molecular machines. In this paper, we perform a comprehensive study of small stochastic systems governed by an underdamped Langevin equation and driven out of equilibrium by a time-delayed continuous feedback control. In their normal operating regime, these systems settle in a nonequilibrium steady state in which work is permanently extracted from the surrounding heat bath. By using the Fokker-Planck representation of the dynamics, we derive a set of second-law-like inequalities that provide bounds to the rate of extracted work. These inequalities involve additional contributions characterizing the reduction of entropy production due to the continuous measurement process. We also show that the non- Markovian nature of the dynamics requires a modification of the basic relation between dissipation and time-reversal symmetry breaking. The new relation includes a contribution arising from the acausal character of the reverse process. This in turn leads to another second-law-like inequality. We illustrate the general formalism by a detailed analytical and numerical study of a harmonic oscillator driven by a linear feedback, which describes actual experimental setups.

The two main contributions of this paper are a proof of concept of the recent novel idea in the area of long-time average cost control, and a new method of overcoming the well-known difficulty of non-convexity of simultaneous optimization of a control law and an additional tunable function. A recently-proposed method of obtaining rigorous bounds of long-time average cost is first outlined for the uncontrolled system with polynomials of system state on the right-hand side. In this method the polynomial constraints are relaxed to be sum-of-squares and formulated as semi-definite programs. It was proposed to use the upper bound of long-time average cost as the objective function instead of the time-average cost itself in controller design. In the present paper this suggestion is implemented for a particular system and is shown to give good results. Designing the optimal controller by this method requires optimising simultaneously both the control law and a tunable function similar to the Lyapunov function. The new approach proposed and implemented in this paper for overcoming the inherent non-convexity of this optimisation is based on a formal assumption that the amplitude of control is small. By expanding the tunable function and the bound in the small parameter, the long-time average cost is reduced by minimizing the respective bound in each term of the series. The derivation of all the polynomial coefficients in controller is given in terms of the solvability conditions of state-dependent linear and bilinear inequalities. The resultant sum-of-squares problems are solved in sequence, thus avoiding the non-convexity in optimization. The proposed approach is implemented for a simple model of oscillatory vortex shedding behind a cylinder.

Many methods have been proposed and tested in the past to obtain an optimal response for step inputs to automatic feedback control systems. Most of these methods have led to the use of sophisticated control devices ranging from small analog to large digital computers. Here the possibility of a simplified switching logic combined with an open-closed loop servomechanism is investigated. Deadbeat response to step inputs was the object of this study rather than a time optimal response. Two types of logic were investigated. A time invariant controller was analyzed, built and tested. The system works on the principle of constant switching times with the output being controlled by an open loop driving voltage which is proportional to the input step size. At the completion of the open loop mode of operation, the system is returned to the normal closed loop mode.

In this article, we consider a fundamental decentralized optimal control problem, which we call the two-player problem. Two subsystems are interconnected in a nested information pattern, and output feedback controllers must be designed for each subsystem. Several special cases of this architecture have previously been solved, such as the state-feedback case or the case where the dynamics of both systems are decoupled. In this paper, we present a detailed solution to the general case. The structure of the optimal decentralized controller is reminiscent of that of the optimal centralized controller; each player must estimate the state of the system given their available information and apply static control policies to these estimates to compute the optimal controller. The previously solved cases benefit from a separation between estimation and control which allows one to compute the control and estimation gains separately. This feature is not present in general, and some of the gains must be solved for simultaneously. We show that computing the required coupled estimation and control gains amounts to solving a small system of linear equations.

Feedback control (based on the quantum continuous measurement) of quantum systems inevitably suffers from estimation delays. In this paper we give a delay-dependent stability criterion for a wide class of nonlinear stochastic systems including quantum spin systems. We utilize a semi-algebraic problem approach to incorporate the structure of density matrices. To show the effectiveness of the result, we derive a globally stabilizing control law for a quantum spin-1/2 systems in the face of feedback delays.

This paper deals with a state feedback H-infinity control problem for linear time-invariant discrete-time descriptor systems with norm-bounded parametric uncertainties. To this end, bounded real lemma (BRL) is extended on the class of uncertain descriptor systems. The control design procedure based on the conditions of BRL for uncertain descriptor systems is proposed. Numerical example is included to illustrate the effectiveness of the present result.

This paper deals with a state feedback H-infinity control problem for linear time-invariant discrete-time descriptor systems with norm-bounded parametric uncertainties. To this end, bounded real lemma (BRL) is extended on the class of uncertain descriptor systems. The control design procedure based on the conditions of BRL for uncertain descriptor systems is proposed. Numerical example is included to illustrate the effectiveness of the present result.

A hierarchical structure of the interlinked programs was developed to provide a flexible computer-aided design tool. A graphical input technique and a data structure are considered which provide the capability of entering the control system model description into the computer in block diagram form. An information storage and retrieval system was developed to keep track of the system description, and analysis and simulation results, and to provide them to the correct routines for further manipulation or display. Error analysis and diagnostic capabilities are discussed, and a technique was developed to reduce a transfer function to a set of nested integrals suitable for digital simulation. A general, automated block diagram reduction procedure was set up to prepare the system description for the analysis routines.

In this paper we propose an output-feedback Model Predictive Control (MPC) algorithm for linear discrete-time systems affected by a possibly unbounded additive noise and subject to probabilistic constraints. In case the noise distribution is unknown, the chance constraints on the input and state variables are reformulated by means of the Chebyshev - Cantelli inequality. The recursive feasibility of the proposed algorithm is guaranteed and the convergence of the state to a suitable neighbor of the origin is proved under mild assumptions. The implementation issues are thoroughly addressed showing that, with a proper choice of the design parameters, its computational load can be made similar to the one of a standard stabilizing MPC algorithm. Two examples are discussed in details, with the aim of providing an insight on the performance achievable by the proposed control scheme.

We propose a time-delayed feedback control scheme for open quantum systems that can dramatically reduce the time to reach steady state. No measurement is performed in the feedback loop, and we suggest a simple all-optical implementation for a cavity QED system. We demonstrate the potential of the scheme by applying it to a driven and dissipative Dicke model, as recently realized in a quantum gas experiment. The time to reach steady state can then reduced by two orders of magnitude for parameters taken from experiment, making previously inaccessible long time attractors reachable within typical experimental run times. The scheme also offers the possibility of slowing down the dynamics, as well as qualitatively changing the phase diagram of the corresponding physical system.

We study the stabilization of a networked control system (NSC) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller. The plant's sensors and actuators are allowed only limited access to the controller at any one time, in a way that is decided on-line using a feedback based communication policy. Our NCS model departs from those in previous formulations in that the controller and plant handle communication disruptions ignoring (in a sense that will be made precise) sensors and actuators that are not actively communicating. We present an algorithm that provides a complete and straightforward method for simultaneously determining stabilizing gains and communication policies and avoids the computational complexity and limitations associated with some previously proposed models. We introduce three feedback-based scheduling policies that quadratically stabilize the closed-loop NCS while achieving various objectives related to the system's rate of convergence, the priorities of different sensors and actuators, and the avoidance of chattering.

This thesis develops an electronic system for the control of motion of different types of active springs, thus improving the performance of mass-spring systems. A mathematical analysis is carried out for various types of active springs. Also, this thesis discusses future design for improving the performance of these electronic circuits to achieve even better performance of mass-spring systems. Keywords include: Ground motion isolation, Josephson junction, Mass-spring system, SQUID amplifier, and Wide-band accelerometer.

This thesis develops an electronic system for the control of motion of different types of active springs, thus improving the performance of mass-spring systems. A mathematical analysis is carried out for various types of active springs. Also, this thesis discusses future design for improving the performance of these electronic circuits to achieve even better performance of mass-spring systems. Keywords include: Ground motion isolation, Josephson junction, Mass-spring system, SQUID amplifier, and Wide-band accelerometer.

This thesis develops an electronic system for the control of motion of different types of active springs, thus improving the performance of mass-spring systems. A mathematical analysis is carried out for various types of active springs. Also, this thesis discusses future design for improving the performance of these electronic circuits to achieve even better performance of mass-spring systems. Keywords include: Ground motion isolation, Josephson junction, Mass-spring system, SQUID amplifier, and Wide-band accelerometer.

We consider using Hamiltonian feedback control to increase the speed at which a continuous measurement purifies (reduces) the state of a quantum system, and thus to increase the speed of the preparation of pure states. For a measurement of an observable with N equispaced eigenvalues, we show that there exists a feedback algorithm which will speed up the rate of state-reduction by at least a factor of 2(N+1)/3.

We consider using Hamiltonian feedback control to increase the speed at which a continuous measurement purifies (reduces) the state of a quantum system, and thus to increase the speed of the preparation of pure states. For a measurement of an observable with N equispaced eigenvalues, we show that there exists a feedback algorithm which will speed up the rate of state-reduction by at least a factor of 2(N+1)/3.

We consider using Hamiltonian feedback control to increase the speed at which a continuous measurement purifies (reduces) the state of a quantum system, and thus to increase the speed of the preparation of pure states. For a measurement of an observable with N equispaced eigenvalues, we show that there exists a feedback algorithm which will speed up the rate of state-reduction by at least a factor of 2(N+1)/3.

ADA481325

ADA481325

Errata tipped in following title page.

Errata tipped in following title page.

Errata tipped in following title page.

Errata tipped in following title page.

Errata tipped in following title page.

146 p. : 29 cm

146 p. : 29 cm

Almost sure asymptotic stabilization of a discrete-time switched stochastic system is investigated. Information on the active operation mode of the switched system is assumed to be available for control purposes only at random time instants. We propose a stabilizing feedback control framework that utilizes the information obtained through mode observations. We first consider the case where stochastic properties of mode observation instants are fully known. We obtain sufficient asymptotic stabilization conditions for the closed-loop switched stochastic system under our proposed control law. We then explore the case where exact knowledge of the stochastic properties of mode observation instants is not available. We present a set of alternative stabilization conditions for this case. The results for both cases are predicated on the analysis of a sequence-valued process that encapsulates the stochastic nature of the evolution of active operation mode between mode observation instants. Finally, we demonstrate the efficacy of our results with numerical examples.

The discrete-time robust repetitive control (RC, or repetitive controller, also designated RC) problem for nonlinear systems is both challenging and practical. This paper proposes a discrete-time output-feedback RC design for a class of systems subject to measurable nonlinearities to track reference robustly with respect to the period variation. The design relies on additive state decomposition, by which the output-feedback RC problem is decomposed into an output-feedback RC problem for a linear time-invariant system and a state-feedback stabilization problem for a nonlinear system. Thanks to the decomposition, existing controller design methods in both the frequency domain and time domain can be employed to make the robustness and discretization for a nonlinear system tractable. To demonstrate the effectiveness, an illustrative example is given.

The discrete-time robust repetitive control (RC, or repetitive controller, also designated RC) problem for nonlinear systems is both challenging and practical. This paper proposes a discrete-time output-feedback RC design for a class of systems subject to measurable nonlinearities to track reference robustly with respect to the period variation. The design relies on additive state decomposition, by which the output-feedback RC problem is decomposed into an output-feedback RC problem for a linear time-invariant system and a state-feedback stabilization problem for a nonlinear system. Thanks to the decomposition, existing controller design methods in both the frequency domain and time domain can be employed to make the robustness and discretization for a nonlinear system tractable. To demonstrate the effectiveness, an illustrative example is given.

Source: Digital Library of India Scanning Centre: Anna University Source Library: '' Date Accessioned: 7/8/2015 15:31 The Digital Library of India was a project under the auspices of the Government of India.

Source: Digital Library of India Scanning Centre: Anna University Source Library: '' Date Accessioned: 7/8/2015 15:31 The Digital Library of India was a project under the auspices of the Government of India.

Source: Digital Library of India Scanning Centre: Anna University Source Library: '' Date Accessioned: 7/8/2015 15:31 The Digital Library of India was a project under the auspices of the Government of India.

We study the possibility of taking bosonic systems subject to quadratic Hamiltonians and a noisy thermal environment to non-classical stationary states by feedback loops based on weak measurements and conditioned linear driving. We derive general analytical upper bounds for the single mode squeezing and multimode entanglement at steady state, depending only on the Hamiltonian parameters and on the number of thermal excitations of the bath. Our findings show that, rather surprisingly, larger number of thermal excitations in the bath allow for larger steady-state squeezing and entanglement if the efficiency of the optimal continuous measurements conditioning the feedback loop is high enough. We also consider the performance of feedback strategies based on homodyne detection and show that, at variance with the optimal measurements, it degrades with increasing temperature.

For quantum systems with linear dynamics in phase space much of classical feedback control theory applies. However, there are some questions that are sensible only for the quantum case, such as: given a fixed interaction between the system and the environment what is the optimal measurement on the environment for a particular control problem? We show that for a broad class of optimal (state-based) control problems (the stationary Linear-Quadratic-Gaussian class), this question is a semi-definite program. Moreover, the answer also applies to Markovian (current-based) feedback.

For quantum systems with linear dynamics in phase space much of classical feedback control theory applies. However, there are some questions that are sensible only for the quantum case, such as: given a fixed interaction between the system and the environment what is the optimal measurement on the environment for a particular control problem? We show that for a broad class of optimal (state-based) control problems (the stationary Linear-Quadratic-Gaussian class), this question is a semi-definite program. Moreover, the answer also applies to Markovian (current-based) feedback.

Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

The manufacturing processes and the control systems for automatic production lines mainly are evaluated through usage of statistical methods as recently machine learning algorithms are also used. The aim of the paper is to present an approach for control measurement systems evaluation, based on a combination of statistical techniques like attribute repeatability & reproducibility analysis, measurement system analysis and supervised machine learning algorithms like random forest and KNN. The proposed method is verified in the production of the G8680x connector, which is used in the automotive industry. The control is performed 100% for all manufactured parts immediately after the “injection molding” process. It is proved that taking advantages of the statistics and machine learning, the manufacturing process and control measurement systems could be evaluated with very high accuracy. The exploration and analysis leads to the formulation of some recommendations in support of process engineers and managers. 

Includes index

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.