Showing papers on "Robustness (computer science) published in 1989"

Adaptive Control: Stability, Convergence and Robustness

Abstract: The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.

Reconfiguration of electric distribution networks for resistive line losses reduction

Abstract: The authors describe a heuristic method for the reconfiguration of distribution networks in order to reduce their resistive line losses under normal operating conditions. The proposed approach is characterized by convergence to the optimum or a near-optimum solution and the independence of the final solution from the initial status of the network switches. The methodology has been implemented in a production-grade computer program, DISTOP (Distribution Network Optimization). The compensation-based power flow technique developed at Pacific Gas and Electric Company for the efficient solution of weakly meshed distribution networks is an essential part of this loss reduction methodology. Important implementation aspects of the methodology and the results of its application to several realistic distribution networks are presented. Numerous test results have indicated that the proposed technique is computationally robust and efficient and, hence, suitable for both planning and operations studies. >

Instability analysis and robust adaptive control of robotic manipulators

Abstract: The robustness of adaptive controllers with respect to uncertainty is examined. The uncertainties include bounded input disturbances, unknown and time-varying plant parameters, and unmodeled dynamics. A simple example shows instability of a recent manipulator control scheme in the presence of bounded disturbances. The adaptive laws for updating the controller parameters are modified so that instabilities are counteracted and robustness is guaranteed. >

The problems of accuracy and robustness in geometric computation

Abstract: Practical implementation of geometric operations remains error-prone, and the goal of implementing correct and robust systems for carrying out geometric computation remains elusive. The problem is variously characterized as a matter of achieving sufficient numerical precision, as a fundamental difficulty in dealing with interacting numeric and symbolic data, or as a problem of avoiding degenerate positions. The author examines these problems, surveys some of the approaches proposed, and assesses their potential for devising complete and efficient solutions. He restricts the analysis to objects with linear elements, since substantial problems already arise in this case. Three perturbation-free methods are considered: floating-point computation, limited-precision rational arithmetic, and purely symbolic representations. Some perturbation approaches are also examined, namely, representation and model, altering the symbolic data, and avoiding degeneracies. >

Some comments on magnetotelluric response function estimation

Abstract: A new set of computational procedures are proposed for estimating the magnetotelluric response functions from time series of natural source electromagnetic field variations. These combine the remote reference method, which is effective at minimizing bias errors in the response, with robust processing, which is useful for removing contamination by outliers and other departures from Gauss-Markov optimality on regression estimates. In addition, a nonparametric jackknife estimator for the confidence limits on the response functions is introduced. The jackknife offers many advantages over conventional approaches, including robustness to heterogeneity of residual variance, relative insensitivity to correlations induced by the spectral analysis of finite data sequences, and computational simplicity. These techniques are illustrated using long-period magnetotelluric data from the EMSLAB Lincoln line. The paper concludes with a cautionary note about leverage effects by high power events in the dependent variables that are not necessarily removable by any robust method based on regression residuals.

Deterministic control of uncertain systems

Abstract: In the deterministic control of uncertain multivariable systems robust closed-loop control is achieved for a specified magnitude range of a class of parameter variations and disturbances. These nonlinear time-varying systems employ nonlinear control functions. The two main approaches are Lyapunov control and variable structure control. The development of the theory of this latter class of control systems will be briefly reviewed here and particular reference will be made to the eigenstructure assignment approach. The use of a CAD package VASSYD allows for straightforward design and simulation studies. Desirable robustness and invariance properties are readily obtained.

Robust control system design with a proportional integral observer

Abstract: A design method for a robust controller including a new type of observer called the proportional integral observer (PI observer) is proposed. The new observer differs from the conventional one by an integration path which provides additional degrees of freedom. This freedom can be used to make the observer-based controller design less sensitive to parameter variation of the system. It is shown that some of the difficulties that may arise in the exclusive pursuit of a design for the conventional observer-based controller from the point of view of system robustness are resolved in a straightforward manner using the PI observer. A systematic robustness recovery procedure is described for the PI observer-based controller design which asymptotically achieves the same loop transfer functions as the full-state feedback control implementation. A design example is included and the effectiveness of our method is illustrated by simulation results.

On the Robustness of ILU Smoothing

Abstract: In the present paper, a detailed analysis of a multigrid method with an ILU smoother applied to a singularly perturbed problem is given. Based on the analysis of a simple anisotropic model problem, a variant of the usual incomplete LU factorization is introduced, which is especially suited as robust smoother. For this variant a detailed analysis and a proof of robustness is given. Furthermore, some contradictions between the smoothing rates predicted by local Fourier analysis and the practically observed convergence factors are explained (see [W. Hackbusch, Multi-grid Methods and Applications, Springer-Verlag, Berlin, Heidelberg, 1985; R. Kettler, “Analysis and comparison of relaxation schemes in robust multi-grid and preconditioned conjugate gradient methods,” in Multi-grid Methods, Lecture Notes in Math. 960, Springer-Verlag, Berlin, 1982; C. A. Thole, Beitrage zur Fourieranalyse von Mehrgitterver fahren, Diplomarbeit, Universitat Bonn, 1983]. The theoretical results are confirmed by numerical tests.

Approaches to robust pole assignment

Abstract: Robust pole assignment is a non-linear optimization problem in many variables. We describe numerical methods for determining robust or well-conditioned so-lutions to the problem of pole assignment by state feedback. The solutions are chosen to minimize various objective functions based on the condition number of the eigenvector matrix. Careful choice of parametrization and objective function avoids singularities and artificial variable constraints; explicit formulae for the gradient and hessian permit rigorous stopping criteria and rapid local convergence. Several computational examples are included.

Model error concepts in control design

Abstract: Traditional modelling notions presume the existence of a ‘truth’ model that relates the input to the output, without advanced knowledge of the input. This has led to the evolution of education and research approaches (including the available control and robustness theories) that treat the modelling and control design as separate problems. This paper explores the subtleties of this presumption. A detailed study of the nature of the modelling errors is useful to gain insight into the limitations of traditional control and identification points of view. Modelling errors need not be ‘small’ but simply ‘appropriate’ for control design. Furthermore, the modelling and control design processes are inevitably iterative in nature.

Robustness in Identification and Control

Abstract: Robustness in identification.- Comments on model validation as set membership identification.- SM identification of model sets for robust control design from data.- Robust identification and the rejection of outliers.- Semi-parametric methods for system identification.- Modal robust state estimator with deterministic specification of uncertainty.- The role of experimental conditions in model validation for control.- Modeling and validation of nonlinear feedback systems.- Towards a harmonic blending of deterministic and stochastic frameworks in information processing.- Suboptimal conditional estimators for restricted complexity set membership identification.- Worst-case simulation of uncertain systems.- On performance limitations in estimation.- Design criteria for uncertain models with structured and unstructured uncertainties.- Robustness and performance in adaptive filtering.- Nonlinear identification based on unreliable priors and data, with application to robot localization.- Robust model predictive control: A survey.- Intrinsic performance limits of linear feedback control.- Puzzles in systems and control.- Robust regional pole placement: An affine approximation.- On achieving L p (?p) performance with global internal stability for linear plants with saturating actuators.- Control under structural constraints: An input-output approach.- Multi-objective MIMO optimal control design without zero interpolation.- Robustness synthesis in l 1: A globally optimal solution.- Optimal control of distributed arrays with spatial invariance.- Numerical search of stable or unstable element in matrix or polynomial families: A unified approach to robustness analysis and stabilization.- A convex approach to a class of minimum norm problems.- Quantified inequalities and robust control.- Dynamic programming for robust control: Old ideas and recent developments.- Robustness of receding horizon control for nonlinear discrete-time systems.- Nonlinear representations and passivity conditions in discrete time.- Robust ripple-free output regulation and tracking under structured or unstructured parameter uncertainties.- An experimental study of performance and fault-tolerance of a hybrid free-flight control scheme.

CAGD-based computer vision

Abstract: The authors explore the connection between CAGD (computer-aided geometric design) and computer vision. A method for the automatic generation of recognition strategies based on the 3-D geometric properties of shape has been devised and implemented. It uses a novel technique to quantify the following properties of features which compose models used in computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this information, the automatic synthesis of a specialized recognition scheme, called a strategy tree, is accomplished. Strategy trees describe, in a systematic and robust manner, the search process used for recognition and localization of particular objects in the given scene. The consist of selected 3-D features which satisfy system constraints and corroborating evidence subtrees which are used in the formation of hypotheses. Verification techniques, used to substantiate or refute these hypotheses are explored. Experiments utilizing 3-D data are presented. >

Control dynamics of speed drive systems using sliding mode controllers with integral compensation

Abstract: The control dynamics and robustness improvement of vector controlled AC speed drive systems using a sliding mode control with integral compensation (SLMC-I) are described. The dynamics of step command speed and impact load disturbance under SLMC-I control are formulated and studied. Acceleration estimation techniques using observers and nonideal differentiators for the SLMC-I speed drive systems are outlined and compared. The control dynamics of SLMC-I with increased system order are discussed. The techniques of robustness improvement for the SLMC-I drives are presented. A method of control in which the sliding line is fed forward is developed to enhance the drive robustness. The control dynamics with this method of control are investigated. The effectiveness of the proposed scheme is demonstrated through computer simulations and experimental work. >

Shaping command input to minimize unwanted dynamics

Abstract: A sequence of impulses is determined which eliminates unwanted dynamics of a dynamic system. This impulse sequence is convolved with an arbitrary command input to drive the dynamic system to an output with a minimum of unwanted dynamics. The input sequence is time optimal in that it constitutes the shortest possible command input that results in no unwanted dynamics of the system subject to robustness and implementation constraints. The preshaping technique is robust under system parameter uncertainty and may be applied to both open and closed loop systems.

A method for finding a pair of multiple load flow solutions in bulk power systems

Abstract: The authors discovered that the convergent characteristic of load flow calculation by the Newton-Raphson method in rectangular coordinates has a unique linearity. It tends to converge straight toward two multiple solutions when they are located close to each other. On the basis of this feature, the authors propose a method for solving two close solutions in bulk power systems. The results of applying this method to a heavily loaded practical 233-bus system and the Klos-Kerner 11-bus system verify its robustness and ability to find solutions successfully and quickly. The proposed method is so fast that it can be applied to an online voltage security system. >

Designing Application-Specific Neural Networks Using the Genetic Algorithm

Abstract: We present a general and systematic method for neural network design based on the genetic algorithm. The technique works in conjunction with network learning rules, addressing aspects of the network's gross architecture, connectivity, and learning rule parameters. Networks can be optimized for various application-specific criteria, such as learning speed, generalilation, robustness and connectivity. The approach is model-independent. We describe a prototype system, NeuroGENESYS, that employs the backpropagation learning rule. Experiments on several small problems have been conducted. In each case, NeuroGENESYS has produced networks that perform significantly better than the randomly generated networks of its initial population. The computational feasibility of our approach is discussed.

Robust stability of interval matrices

Abstract: Sufficient conditions for the Hurwitz and Schur stability of interval matrices are reviewed with some simplifications and some new results. The necessary and sufficient conditions for the Hurwitz and Schur stability of 2*2 matrices are determined. For general m*n interval matrices the pseudodivision method is applied for (2n-4)-dimensional faces for continuous systems and for (2n-2)-dimensional faces for discrete systems as well as for the corresponding lower dimensional faces. The method is applicable to low-dimensional matrices, e.g., n=3 or n=4. For higher dimensions numerical and computational problems arise. >

Robust set operations on polyhedral solids

Abstract: An algorithm for performing regularized Boolean operation on polyhedral solids is described. Robustness is achieved by adding symbolic reasoning as a supplemental step to resolve possible numerical uncertainty. Additionally, numerical redundancy and numerical computation based on derived quantities are reduced as much as possible. Experience with an implementation of the algorithm, using a unit-cube example as a simple test object for robustness, is discussed. >

New generalized structural filtering concept for active vibration control synthesis

Abstract: A new concept of generalized structural filtering and its application to active vibration control synthesis are presented. .The concept is a natural extension of the classical notch and phase-lead/-lag filtering, and emphasizes the use of a nonminimum-phase filter, which has zeros in the right-half s plane. Application of this concept to single-input/singleoutput systems with many oscillatory modes results in a robust feedback compensator with much physical insight. The concept also enables the control designer to understand the inherent nature of an "optimal" compensator and to modify the optimal design to be more robust and meaningful. This paper shows that, for certain cases, nonminimumphase structural filtering provides the proper phase lag to increase the closed-loop damping of the flexible modes while maintaining good performance and robustness to parameter variations.

CFAR detection for multiple target situations

Abstract: In the paper, three detectors are proposed and studied in the presence of interfering targets in the reference cells. In the weighted cell-averaging constant false-alarm rate (WCA-CFAR) detector the means generated by the leading and the lagging range cells are weighted in accordance with the level of the interference. Optimum weights that maintain CFAR are obtained while the probability of detection is maximised. The censored mean level detector (CMLD) is considered next, this requires exact knowledge of the number of interfering targets. The detection performance of the CMLD is studied for Swerling IV targets and compared to that with Swerling II targets. Then, the generalised censored mean-level detector (GCMLD) is proposed. The GCMLD does not require a priori knowledge of the number of interfering targets and achieves robust performance. The number of interfering targets is determined and their corresponding samples are then censored. Exact expressions for the probability of censoring the interfering targets and the overall probability of detection are derived. A comparison of the performance of the GCMLD with that of a recently proposed CFAR detector is also presented to demonstrate the robustness of the GCMLD.

Robust Controller Design for a Nonlinear CSTR

Abstract: A design methodology is presented for the analysis and synthesis of robust linear controllers for a nonlinear continuous stirred tank reactor. Regions are defined in the phase plane in which the maintenance of robust stability and the achievement of robust performance levels are guaranteed. The results are based upon new extensions of the structured singular value theory to a class of nonlinear and time-varying systems.

Robust isolable models for failure diagnosis

Abstract: The paper presents a design procedure to generate parity equation models for analytical failure detection and isolation. The models are in “statistically-isolable” structure that prevents incorrect isolation decisions under marginal failure size if the residuals are tested in parallel. Of the combinatorial multitude of structurally-suitable models, a choice is made on the basis of sensitivities with respect to different failures and robustness relative to uncertainties in selected parameters of an underlying model. A complete set of parity equations fitting the isolable structure is first generated from a state-space model. The equations unsuitable for sensitivity are eliminated, and a suboptimally-robust diagnostic model is obtained in a constrained discrete search over the remaining set.

The frequency decomposition multi-grid method

Abstract: A new variant of the multi-grid algorithms is presented. It uses multiple coarse-grid corrections with particularly associated prolongations and restrictions. In this paper the robustness with respect to anisotropic problems is considered.

Pole-placement designs of power system stabilizers

Abstract: This paper examines four pole placement techniques applied to the design of power system stabilizers. These methods are the full state feedback, an output feedback by the projective method [1], a design based on a full order observer, and a low order dynamic compensator also based on the projective method [2]. A single machine infinite bus power system is used to illustrate the different design approaches. The power system stabilizer is designed to provide damping to the local mode of this system. It is shown that in order to provide the same amount of damping improvement, the power system stabilizers designed using the different methods have similar gains and plases at the modal frequency, Figure 1. This result is explained by establishing a link between the frequency modal response method and the close-loop system electromechnical modes. The response of the dynamic controllers with modes close to the local mode is also investigated. It is shown that this situation causes a resonant condition which, in general, should be avoided. This paper also presents a simple robust damping controller design considering two different operating conditions of the power system: a weak connection case and a strong connection case. The robust controller is based on the reduction of two controllers using a Hankel-Norm model reduction algorithm [3].

The closest unstable equilibrium point method for power system dynamic security assessment

Abstract: The closest unstable equilibrium point (u.e.p.) method is an important tool for problems associated with power system dynamic security assessment. A study is made of the closest u.e.p. method from both theoretical and computational points of view. Issues regarding the existence and uniqueness of the closest u.e.p. are investigated. A dynamical characterization of the closest u.e.p. is derived, and the problem of its robustness with respect to changes in different parameters of a power system is studied. This robustness property highlights the practical applicability of the closest u.e.p. method to power system dynamic security assessment. An improved closest u.e.p. method is then proposed on the basis of theoretical results which uses a reduced model approach and is shown to be optimal, in the sense that the estimated stability region characterized by the corresponding energy function is the largest one within the entire stability region. Examples are given to illustrate the robustness of the closest u.e.p. and improved closest u.e.p. methods. >