Showing papers on "Observer (quantum physics) published in 1997"

An observer looks at synchronization

Abstract: In the literature on dynamical systems analysis and the control of systems with complex behavior, the topic of synchronization of the response of systems has received considerable attention. This concept is revisited in the light of the classical notion of observers from (non)linear control theory,.

Radiology's Achilles' heel: error and variation in the interpretation of the Röntgen image.

Abstract: The performance of the human eye and brain has failed to keep pace with the enormous technical progress in the first full century of radiology. Errors and variations in interpretation now represent the weakest aspect of clinical imaging. Those interpretations which differ from the consensus view of a panel of "experts" may be regarded as errors; where experts fail to achieve consensus, differing reports are regarded as "observer variation". Errors arise from poor technique, failures of perception, lack of knowledge and misjudgments. Observer variation is substantial and should be taken into account when different diagnostic methods are compared; in many cases the difference between observers outweighs the difference between techniques. Strategies for reducing error include attention to viewing conditions, training of the observers, availability of previous films and relevant clinical data, dual or multiple reporting, standardization of terminology and report format, and assistance from computers. Digital acquisition and display will probably not affect observer variation but the performance of radiologists, as measured by receiver operating characteristic (ROC) analysis, may be improved by computer-directed search for specific image features. Other current developments show that where image features can be comprehensively described, computer analysis can replace the perception function of the observer, whilst the function of interpretation can in some cases be performed better by artificial neural networks. However, computer-assisted diagnosis is still in its infancy and complete replacement of the human observer is as yet a remote possibility.

A systematic approach to adaptive observer synthesis for nonlinear systems

Abstract: Geometric techniques of controller design for nonlinear systems have enjoyed great success. A serious shortcoming, however, has been the need for access to full-state feedback. This paper addresses the issue of state estimation from limited sensor measurements in the presence of parameter uncertainty. An adaptive nonlinear observer is suggested for Lipschitz nonlinear systems, and the stability of this observer is shown to be related to finding solutions to a quadratic inequality involving two variables. A coordinate transformation is used to reformulate this inequality as a linear matrix inequality. A systematic algorithm is presented, which checks for feasibility of a solution to the quadratic inequality and yields an observer whenever the solution is feasible. The state estimation errors then are guaranteed to converge to zero asymptotically. The convergence of the parameters, however, is determined by a persistence-of-excitation-type constraint.

Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems

Abstract: In this paper, convergence analysis of the extended Kalman filter (EKF), when used as an observer for nonlinear deterministic discrete-time systems, is presented. Based on a new formulation of the first-order linearization technique, sufficient conditions to ensure local asymptotic convergence are established. Furthermore, it is shown that the design of the arbitrary matrix plays an important role in enlarging the domain of attraction and then improving the convergence of the modified EKF significantly. The efficiency of this approach, compared to the classical version of the EKF, is shown through a nonlinear identification problem as well as a state and parameter estimation of nonlinear discrete-time systems.

Sensorless current mode control-an observer-based technique for DC-DC converters

Abstract: Sensorless current mode (SCM) control is an observer method that provides the operating benefits of current mode control without current sensing. SCM has significant advantages over both conventional peak and average current-mode control techniques in noise susceptibility and dynamic range. The method supports both line and bulk load regulation, and reduces control complexity to a single loop. The static and dynamic performance of SCM are analyzed and verified experimentally for DC-DC converters. Performance in continuous and discontinuous modes compares favorably to conventional techniques when noise is not a factor, but is significantly better when noise and wide load ranges are a concern. The SCM method encompasses one-cycle control as a special case; the general SCM method is introduced here as a public domain control technique.

A separation principle for the stabilization of a class of nonlinear systems

Abstract: It is shown that the performance of a globally bounded partial state feedback control of an input-output linearizable system can be recovered by a sufficiently fast high-gain observer. The performance recovery includes recovery of asymptotic stability of the origin, the region of attraction. and trajectories.

Nonlinear observer design using Lyapunov's auxiliary theorem

Abstract: The work proposes an approach to the nonlinear observer design problem. Based on the early ideas that influenced the development of the linear Luenberger observer theory, the proposed approach develops a nonlinear analogue. The formulation of the observer design problem is realized via a system of first-order linear singular PDEs, and a rather general set of necessary and sufficient conditions for solvability is derived by using Lyapunov's auxiliary theorem. The solution to the above system of PDEs is locally analytic and this enables the development of a series solution method, that is easily programmable with the aid of a symbolic software package. Within the proposed design framework, both full-order and reduced-order observers are studied.

Repetitive and adaptive control of robot manipulators with velocity estimation

Abstract: This paper presents repetitive and adaptive motion control schemes for rigid-link robot manipulators, when the manipulator's joint velocities cannot be measured by the control system. The control objective consists in tracking a prescribed desired trajectory. In the case of repetitive control, the desired trajectory is periodic and it is required that the robot achieve the control objective through repeated learning trials. We assume that the robot inverse dynamics are totally unknown, except that they can be represented by an integral of the product of known differentiable kernel and an unknown influence function. In the case of adaptive control, it is assumed that only the manipulator inertia parameters are unknown and that the desired trajectory jerks are available to the control system. In both control schemes, a velocity observer, which is formulated based on the desired input/output relation of the manipulator, is used to estimate the manipulator joint velocities. A stability analysis of the repetitive and adaptive control schemes with velocity estimation is presented. Simulation and experimental results show that the proposed repetitive control algorithm is successful in achieving the control objective without direct measurement of the joint velocities.

Approximate set-valued observers for nonlinear systems

Abstract: A set-valued observer (SVO) produces a set of possible states based on output measurements and a priori models of exogenous disturbances and noises. Previous work considered linear time-varying systems and unknown-but-bounded exogenous signals. In this case, the sets of possible state vectors take the form of polytopes whose centers are optimal state estimates. These polytopic sets can be computed by solving several small linear programs. An SVO can be constructed conceptually for nonlinear systems; however, the set of possible state vectors no longer takes the form of polytopes, which in turn inhibits their explicit computation. This paper considers an "extended SVO". As in the extended Kalman filter, the state equations are linearized about the state estimate, and a linear SVO is designed along the linearization trajectory. Under appropriate observability assumptions, it is shown that the extended SVO provides an exponentially convergent state estimate in the case of sufficiently small initial condition uncertainty and provides a nondivergent state estimate in the case of sufficiently small exogenous signals.

Dynamic stabilization of regular linear systems

Abstract: We consider a general class of infinite-dimensional linear systems, called regular linear systems, for which convenient representations are known to exist both in time and in frequency domain. For this class of systems, we investigate the concepts of stabilizability and detectability, in particular, their invariance under feedback and their relationship to exponential stability. We introduce two concepts of dynamic stabilization, the first formulated as usual, with the plant and the controller connected in feedback, and the second with two feedback loops. Even for finite-dimensional systems, the second concept, stabilization with an internal loop in the controller, is more general. We argue that the more general concept is the natural one, and we derive sufficient conditions under which an observer-based stabilizing controller with an internal loop can be constructed.

An adaptive high-gain observer for nonlinear systems

Abstract: In this paper we present a high-gain observer for a general class of nonlinear SISO systems for which the high-gain parameter is determined on-line in an adaptive fashion. The adaptation scheme is simple and universal in the sense that it is independent of the system the observer is designed for. We prove that the observer output error becomes smaller than a user specified bound for large times and that the adaptation converges. The assumptions required for the adaptive high-gain observer are the same as for the nonadaptive high-gain observer, namely that the system is uniformly observable for any u(t).

A closed-form solution to bearings-only target motion analysis

Abstract: Bearings-only target motion analysis is a nonlinear state estimation problem in which the noise corrupted angle of arrival measurements of an emitted signal are used to obtain estimates of the source's range, bearing, course, and speed. The estimation process is complicated by unusual observability properties that render the quality of the estimate highly dependent on both the measurement noise levels and the source-observer geometry. Solutions that use recursive Kalman filtering approach or batch-style algorithms have been reported. The nonlinear batch style estimators for this process require iterative solution methods and under certain scenarios can be sensitive to initial conditions. Pseudolinear solutions that alleviate some of the difficulties with the iterative batch algorithms have been proposed. Although early versions of the pseudolinear filter suffered from biased estimates, subsequent improvements appear to have reduced the bias problem. This paper discusses a new pseudolinear solution based on the observable parameters from individual data segments defined by periods of constant observer velocity (termed "legs"). This solution is a true closed-form solution to the bearings-only target motion analysis problem. Although theoretically interesting, the technique does suffer under conditions of poor observability. A practical pseudolinear estimate, that does not suffer from the same observability problems, is developed and related to the first solution. Algorithm performance results, obtained from computer simulation, are presented. For the scenarios examined, the technique provides good state estimates under conditions of high observability. As observability conditions deteriorate, the solution does develop biases. However, it may still be useful for initializing an iterative nonlinear batch-style estimation algorithm.

Implementation of a friction estimation and compensation technique

Abstract: A friction estimation and compensation technique was implemented on a laboratory apparatus designed to permit the direct measurement of friction. Experimental results are reported for a friction observer which estimates total friction present assuming it to be a constant times the sign of velocity. A second observer is used to estimate the velocity using the measured position of the rotating shaft in the apparatus, when velocity is not measurable. Experimental results show that the friction estimate is consistent with the measured friction, displaying the theoretical hysteresis phenomenon. Moreover, the performance of the system is substantially improved by the use of the estimated friction to compensate the system, especially at very low velocity.

An information theoretic approach to observer path design for bearings-only tracking

Abstract: Open-loop control strategies, via information theoretic criteria, for the design of optimal observer trajectories in the bearings-only tracking problem are presented. The aim is to obtain tight bounds on the location and velocity of a single target through own ship maneuvers. In this paper, optimal paths are derived by maximizing the mutual information between the measurement sequence and the final target state or the entire target trajectory. Optimization techniques, such as dynamic programming and enumeration with optimal pruning are derived.

Discrete-time observability and estimability analysis for bearings-only target motion analysis

Abstract: Observability in the context of bearings-only tracking (BOT) is still the subject of important literature. Different from previous approaches, where continuous-time analysis was considered, our approach relies on discrete-time analysis. It is then shown that this allows us to use directly and efficiently the simple formalisms of linear algebra. Using the direct approach, observability analysis is essentially reduced to basic considerations about subspace dimensions. Even if this approach is conceptually quite direct, it becomes more and more complex as the source-encounter scenario complexity increases. For complex scenarios, the dual approach may present some advantages essentially due to the direct use of multilinear algebra. New results about BOT observability for maneuvering sources are thus obtained. Observability analysis is then extended to unknown instants of source velocity changes. Even if observability analysis provides thorough insights about the algebraic structure of the BOT problem, the optimization of the observer maneuvers is essentially a control problem. Basic algebraic considerations prove that a relevant cost functional for this control problem is the determinant of the Fisher information matrix (FIM). So, a large part of this work is devoted to the analysis of this cost functional. Using multilinear algebra, general approximations of this functional are given. In order to involve only directly estimable parameters, the source bearing-rates are examined. Using these approximations, a general framework for optimizing the observer trajectory is derived which allow us to approximate the optimal sequence of controls. It is worth stressing that our approach does not require the knowledge of the source trajectory parameters and is still valid for a maneuvering source.

On the Synchronization of Chaos Systems by Using State Observers

Abstract: We show that the synchronization of chaotic systems can be achieved by using the observer design techniques which are widely used in the control of dynamical systems. We prove that local synchronization is possible under relatively mild conditions and global synchronization is possible if the chaotic system has some special structures, or can be transformed into some special forms. We show that some existing synchronization schemes for chaotic systems are related to the proposed observer-based synchronization scheme. We prove that the proposed scheme is robust with respect to noise and parameter mismatch under some mild conditions. We also give some examples including the Lorenz and Rossler systems and Chua's oscillator which are known to exhibit chaotic behavior, and show that in these systems synchronization by using observers is possible.

Observer-based controllers for fractional differential systems

Abstract: The goal of this paper is to propose observer-based controllers, either in state-space form or in polynomial representation, for fractional differential systems. As for linear differential systems of integer order, polynomial representation allows us to take advantage of the Youla parametrization in order to asymptotically reject some perturbations. This is illustrated on a worked-out example.

Nonlinear path control in automated vehicle guidance

Abstract: The problem of path control of automatically guided vehicles along a desired trajectory is considered where both lateral and longitudinal dynamics have been incorporated in the vehicle model. It is shown that a nonlinear decoupling controller and pole-placement can be used to obtain a closed-loop behavior that is independent of the vehicle operation point. For the pole-placement, the entire state is necessary. Since the sideslip is not available from measurements, an observer is applied, estimating the sideslip. Due to the steady state errors imposed by the nonlinear controller, a predictive filter is used to calculate this steady state error. The effectiveness of this controller is then demonstrated by simulations.

Adaptive nonlinear output feedback tracking with a partial high-gain observer and backstepping

Abstract: An adaptive output feedback controller for nonlinear systems with nonlinearities depending on the first r (1/spl les/r/spl les/n) derivatives of the output is proposed. The derivatives are estimated with a partial state high-gain observer, and the remaining states are handled using a backstepping method. Compared with methods based on full state high-gain observer, this approach improves robustness with respect to measurement noise and avoids overparametrization. Semiglobal tracking is proven under the assumption that the regressor is persistently exciting.

On nonlinear continuous observers

Abstract: The paper investigates the possibility of using smooth maps with continuous inverses (which are called semi-diffeomorphisms here) for the study of observability and observer design for nonlinear smooth systems. A method is proposed for the design of continuous observers for uniformly observable nonlinear systems. The results obtained also cover systems not coverable by all previous results on smooth nonlinear observers.

The Quantum Theory of Measurement (2nd edn)

Abstract: The newly revised edition of this well-known book categorizes prevalent views on measurement as described by quantum mechanics, discusses basics agreed to by many who on other issues disagree, and describes some of the problems. Although many paragraphs rest unchanged from the first (1991) edition, results found since 1991 are used to reorganize and sharpen the focus of the book, so that even the old paragraphs are now understood differently and more clearly. One advance in the second edition is a new and more general no-go theorem; another is separation of formal derivations from interpretation. The dozen or so definitions essential to following the book even casually are stated clearly. By this means the authors succeed pretty well in achieving their stated desire to make the book comprehensible to those who do not share their philosophic predispositions. While I differ in philosophy from the authors, attending to their discussion uncovered weaknesses in my own thinking and improved it. The mathematical language of quantum mechanics expresses a system under measurement by states (as rays in a Hilbert space) and a hamiltonian operator, distinct from the apparatus that produces outcomes, which is expressed by a positive operator-valued (POV) measure. In this way quantum language separates state preparation from state measurement. Often the Hilbert space is viewed as a tensor product of subspaces, allowing further conceptual separations. The authors take the stance that quantum mechanics calls for splitting the empirical world into parts, the most essential being (1) objective systems S (to be observed) and (2) apparatus A (preparation and registration devices that produces outcomes (or, as the authors write, definite pointer values) of the observed system). In some interpretations, one or both of an observer and an environment appear as additional parts. What is to be included in the system S versus the apparatus A is not specified by the language, but is open to the theoretician; a probe, for example, can be analysed as either part of the apparatus or as part of the system, as was discussed by von Neumann in work cited by the authors. With what should a theory of measurement be concerned? A broad division of approaches is defined by how one answers the question: should one try to do away with the cut between measuring apparatus and system? The authors phrase this as a choice of REFERENT, a term which in my mind puts them on shaky semantic ground; anyway The Quantum Theory of Measurement is concerned with implications of the `yes'. The book unfolds with the power of a tragedy, in which the logical consequences lead, step-by-step, to the statement and proof of theorem 6.2.1, which, roughly speaking, asserts the non-existence of a solution to the problem of getting definite pointer values from measuring apparatus that exhibits the superposition demanded by its description as a quantum system. Possible responses to this theorem are discussed, among them the many-worlds interpretation and a modification of quantum mechanics that elevates decoherence to a principle. Citations of the literature are thorough, and many points of view are crisply summarized. The book is indispensable to both those who work in the broad direction chosen by the authors and to those who wish to set any other direction in context.