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Juang, J.-N.

Publications and source records attributed to Juang, J.-N..

At least 19 records

Validation of an Experimentally Derived Uncertainty Model

The results show that uncertainty models can be obtained directly from system identification data by using a minimum norm model validation approach. The error between the test data and an analytical nominal model is modeled as a combination of unstructured additive and structured input multiplicative uncertainty. Robust controllers which use the experimentally derived uncertainty model show significant stability and performance improvements over controllers designed with assumed ad hoc uncertainty levels. Use of the identified uncertainty model also allowed a strong correlation between design predictions and experimental results.

Lim, K. B.

Vibration suppression using a constrained rate-feedback-threshold control strategy

A finite time, minimum force rate-feedback-threshold controller is developed to bring a system with or without known external disturbances back into an 'allowable' state bound in finite time. The disturbances are assumed to be expandable in terms of Fourier series. The optimal control is defined by a two-point boundary value problem coupled to a set of definite integral constraints. Quasi-closed form solutions are derived which replace the solution of the two-point boundary value problem and definite integral constraints with the solution of algebraic equations and the calculation of matrix exponentials. Examples are provided which demonstrate the threshold control technique and compare the quasi-closed form solutions with numerical and MACSYMA generated exact solutions.

Zimmerman, D. C.

Comparison of several system identification methods for flexible structures

In the last few years various methods of identifying structural dynamics models from modal testing data have appeared. This paper presents a comparison of four of these algorithms: the Eigensystem Realization Algorithm (ERA), the modified version ERA/DC where DC indicates that it makes use of data correlations, the Q-Markov Cover algorithm, and an algorithm due to Moonen, DeMoor, Vandenberghe and Vandewalle. The comparison is made using a five mode computer model of the 20 meter Mini-Mast truss structure at NASA Langley Research Center, and various noise levels are superimposed to produce simulated data. The results show that for the example considered ERA/DC generally gives the best results; that ERA/DC is always at least as good as ERA which is shown to be a special case of ERA/DC; that Q-Markov requires the use of significantly more data than ERA/DC to produce comparable results; and that in some situations Q-Markov cannot produce comparable results.

Lew, J.-S.

Recent developments in learning control and system identification for robots and structures

This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

Phan, M.

Robust eigenstructure assignment by a projection method - Applications using multiple optimization criteria

A methodology for robust eigenstructure assignment for multivariable feedback systems is presented. The algorithm is based upon a pole placement technique using projections onto subspaces of admissible eigenvectors. New ideas are introduced to generate target (desired) sets of unitary eigenvectors and determine optimal feasible eigenvectors in a least-square sense. Useful connections are established between the pole-placement by independent modal space control and the method introduced in this paper. A multicriterion optimization algorithm is also presented, which takes efficient advantage of the present eigenstructure assignment method. These developments show significant improvement over an earlier version of this algorithm in both computational cost and accuracy. This optimization process appears to be numerically robust and suitable for high-dimensional multicriterion optimizations; it is especially attractive for computer-aided design of control systems.

Rew, D. W.

Design of optimally normal minimum gain controllers by continuation method

A measure of the departure from normality is investigated for system robustness. An attractive feature of the normality index is its simplicity for pole placement designs. To allow a tradeoff between system robustness and control effort, a cost function consisting of the sum of a norm of weighted gain matrix and a normality index is minimized. First- and second-order necessary conditions for the constrained optimization problem are derived and solved by a Newton-Raphson algorithm imbedded into a one-parameter family of neighboring zero problems. The method presented allows the direct computation of optimal gains in terms of robustness and control effort for pole placement problems.

Lim, K. B.

Learning control for slewing of a flexible panel

This paper studies the applicability of a discrete-time learning control method to the slewing control of a large flexible panel. Among the issues discussed are feasibility of the desired trajectories and their specification schemes, learning control by linear feedback, limitation of the actuator device output, and robustness to parameter changes or modeling errors associated with the chosen learning control design. To demonstrate the effectiveness of learning control, the system is designed with a proportional controller of the base angle only. Then application of the learning control is shown to make the system learn quickly to achieve the desired slewing without residual vibration at the end of the maneuver. Simulation results are reported and discussed.

Phan, M.

A comparative overview of modal testing and system identification for control of structures

A comparative overview is presented of the disciplines of modal testing used in structural engineering and system identification used in control theory. A list of representative references from both areas is given, and the basic methods are described briefly. Recent progress on the interaction of modal testing and control disciplines is discussed. It is concluded that combined efforts of researchers in both disciplines are required for unification of modal testing and system identification methods for control of flexible structures.

Juang, J.-N.

A brief review on the identification of nonlinear mechanical systems

This paper presents a brief review of the disciplines used in the identification of nonlinear mechanical systems, including the detection of nonlinearities and their quantification, and parameter estimation. Techniques for determining the parameters of nonlinear system models with assumed model form are described and briefly discussed. Recent developments in identifying system models which may contain the actual model forms as well as incorrect forms is also briefly described. A list of representative references from structures and control disciplines is given.

Natke, H. G.

Low authority-threshold control for large flexible structures

An improved active control strategy for the vibration control of large flexible structures is presented. A minimum force, low authority-threshold controller is developed to bring a system with or without known external disturbances back into an 'allowable' state manifold over a finite time interval. The concept of a constrained, or allowable feedback form of the controller is introduced that reflects practical hardware implementation concerns. The robustness properties of the control strategy are then assessed. Finally, examples are presented which highlight the key points made within the paper.

Zimmerman, D. C.

Force prediction using singular-value decomposition

Results of a preliminary investigation into a method which can be used to improve the results of an experimental force prediction analysis is presented. The method uses a singular value decomposition technique to reduce measurement noise present in the measured input data matrix. The fundamental theory for the method along with an experimental example is shown. The method is shown to provide encouraging force prediction improvements when the input data matrix contains high levels of measurement noise.

Elliott, K. B.

Vibration suppression using a constrained rate-feedback Threshold control strategy

Quasi-closed form solutions are derived for the finite time, minimum force rate-feedback threshold controller to bring a system with or without known external disturbances back into an 'allowable' state manifold in finite time. The disturbances are assumed to be expandable in terms of Fourier series. The quasi-closed form solutions replace the solution of the two-point boundary value problem and definite integral constraints with the solution of algebraic equations and the calculation of matrix exponentials. Examples demonstrate the threshold control technique and compare the quasi-closed form solutions with MACSYMA generated exact solutions (for small system order) and with the numerical solution of the two-point boundary value problem.

Zimmerman, D. C.

Effects of noise on modal parameters identified by the Eigensystem Realization Algorithm

The basic concept of the Eigensystem Realization Algorithm for modal parameter identification and model reduction is extended to minimize the distortion of the identified parameters caused by noise. The mathematical foundation for the properties of accuracy indicators, such as the singular values of the data matrix and modal amplitude coherence, is provided, based on knowledge of the noise characteristics. These indicators quantitatively discriminate noise from system information and are used to reduce the realized system model to a better approximation of the true model. Monte Carlo Simulations are included to support the analytical studies.

Juang, J.-N.

Effects of atmosphere on slewing control of a flexible structure

Air drag forces are introduced into the equations for a slewing control maneuver of a flexible structure to assess the effects of atmosphere on the controller design. Simulated modal parameters and transient responses are compared with experiments in normal atmosphere and in vacuum. Analytical techniques for control laws are examined and verified. Physical insight into the air damping is gained so that results in vacuum can be extrapolated from results in air.

Juang, J.-N.

The development of optimal control laws for orbiting tethered platform systems

A mathematical model of the open and closed loop in-orbit plane dynamics of a space platform-tethered-subsatellite system is developed. The system consists of a rigid platform from which an (assumed massless) tether is deploying (retrieving) a subsatellite from an attachment point which is, in general, offset from the platform's mass center. A Lagrangian formulation yields equations describing platform pitch, subsatellite tether-line swing, and varying tether length motions. These equations are linearized about the nominal station keeping motion. Control can be provided by both modulation of the tether tension level and by a momentum type platform-mounted device; system controllability depends on the presence of both control inputs. Stability criteria are developed in terms of the control law gains, the platform inertia ratio, and tether offset parameter. Control law gains are obtained based on linear quadratic regulator techniques. Typical transient responses of both the state and required control effort are presented.

Bainum, P. M.

Effects of noise on ERA-identified modal parameters

The basic concept of the Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction is extended to minimize the distortion of the identified parameters caused by noise. The mathematical foundation for the properties of accuracy indicators such as the singular values of the data matrix and modal amplitude coherence is provided based on knowledge of the noise characteristics. These indicators quantitatively discriminate noise from system information and are used to reduce the realized system model to a better approximation of the true model. Monte Carlo simulations are included to support the analytical studies.

Juang, J.-N.