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Horta, Lucas G.

Publications and source records attributed to Horta, Lucas G..

At least 73 records · Page 4

System identification from closed-loop data with known output feedback dynamics

This paper presents a procedure to identify the open loop systems when it is operating under closed loop conditions. First, closed loop excitation data are used to compute the system open loop and closed loop Markov parameters. The Markov parameters, which are the pulse response samples, are then used to compute a state space representation of the open loop system. Two closed loop configurations are considered in this paper. The closed loop system can have either a linear output feedback controller or a dynamic output feedback controller. Numerical examples are provided to illustrate the proposed closed loop identification method.

Phan, Minh↗

System/observer/controller identification toolbox

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

Juang, Jer-Nan↗

Improvement of observer/Kalman filter identification (OKID) by residual whitening

This paper presents a time-domain method to identify a state space model of a linear system and its corresponding observer/Kalman filter from a given set of general input-output data. The identified filter has the properties that its residual is minimized in the least squares sense, orthogonal to the time-shifted versions of itself, and to the given input-output data sequence. The connection between the state space model and a particular auto-regressive moving average description of a linear system is made in terms of the Kalman filter and a deadbeat gain matrix. The procedure first identifies the Markov parameters of an observer system, from which a state space model of the system and the filter gain are computed. The developed procedure is shown to improve results obtained by an existing observer/Kalman filter identification method, which is based on an auto-regressive model without the moving average terms. Numerical and experimental results are presented to illustrate the proposed method.

Phan, Minh↗

On-line identification of forward/inverse systems for adaptive control applications

The paper is concerned with the on-line identification of system Markov parameters using observers. Two types of parameters are sought: the forward system parameters, which provide estimates of the outputs for given inputs, and inverse system parameters, which provide estimates of inputs for given outputs. A procedure is proposed which uses the inverse system to generate commands that produce a desired system response. The feasibility of the procedure is demonstrated using test results from an implementation of a truss structure fitted with piezoelectric actuators and collocated strain gauges.

Horta, Lucas G.↗

Langley's CSI evolutionary model: Phase O

A testbed for the development of Controls Structures Interaction (CSI) technology to improve space science platform pointing is described. The evolutionary nature of the testbed will permit the study of global line-of-sight pointing in phases 0 and 1, whereas, multipayload pointing systems will be studied beginning with phase 2. The design, capabilities, and typical dynamic behavior of the phase 0 version of the CSI evolutionary model (CEM) is documented for investigator both internal and external to NASA. The model description includes line-of-sight pointing measurement, testbed structure, actuators, sensors, and real time computers, as well as finite element and state space models of major components.

Belvin, W. Keith↗

Identification of observer/Kalman filter Markov parameters: Theory and experiments

An algorithm to compute Markov parameters of an observer or Kalman filter from experimental input and output data is discussed. The Markov parameters can then be used for identification of a state space representation, with associated Kalman gain or observer gain, for the purpose of controller design. The algorithm is a non-recursive matrix version of two recursive algorithms developed in previous works for different purposes. The relationship between these other algorithms is developed. The new matrix formulation here gives insight into the existence and uniqueness of solutions of certain equations and gives bounds on the proper choice of observer order. It is shown that if one uses data containing noise, and seeks the fastest possible deterministic observer, the deadbeat observer, one instead obtains the Kalman filter, which is the fastest possible observer in the stochastic environment. Results are demonstrated in numerical studies and in experiments on an ten-bay truss structure.

Juang, Jer-Nan↗

Active vibration absorber for CSI evolutionary model: Design and experimental results

The development of control of large flexible structures technology must include practical demonstration to aid in the understanding and characterization of controlled structures in space. To support this effort, a testbed facility was developed to study practical implementation of new control technologies under realistic conditions. The design is discussed of a second order, acceleration feedback controller which acts as an active vibration absorber. This controller provides guaranteed stability margins for collocated sensor/actuator pairs in the absence of sensor/actuator dynamics and computational time delay. The primary performance objective considered is damping augmentation of the first nine structural modes. Comparison of experimental and predicted closed loop damping is presented, including test and simulation time histories for open and closed loop cases. Although the simulation and test results are not in full agreement, robustness of this design under model uncertainty is demonstrated. The basic advantage of this second order controller design is that the stability of the controller is model independent.

Bruner, Anne M.↗

The Langley Research Center CSI phase-0 evolutionary model testbed-design and experimental results

A testbed for the development of Controls Structures Interaction (CSI) technology is described. The design philosophy, capabilities, and early experimental results are presented to introduce some of the ongoing CSI research at NASA-Langley. The testbed, referred to as the Phase 0 version of the CSI Evolutionary model (CEM), is the first stage of model complexity designed to show the benefits of CSI technology and to identify weaknesses in current capabilities. Early closed loop test results have shown non-model based controllers can provide an order of magnitude increase in damping in the first few flexible vibration modes. Model based controllers for higher performance will need to be robust to model uncertainty as verified by System ID tests. Data are presented that show finite element model predictions of frequency differ from those obtained from tests. Plans are also presented for evolution of the CEM to study integrated controller and structure design as well as multiple payload dynamics.

Belvin, W. K.↗

A velocity command stepper motor for CSI application

The application of linear force actuators for vibration suppression of flexible structures has received much attention in recent years. A linear force actuator consists of a movable mass that is restrained such that its motion is linear. By application of a force to the mass, an equal and opposite reaction force can be applied to a structure. The use of an industrial linear stepper motor as a reaction mass actuator is described. With the linear stepper motor mounted on a simple test beam and the NASA Mini-Mast, output feedback of acceleration or displacement are used to augment the structural damping of the test articles. Significant increases in damping were obtained for both the test beam and the Mini-Mast.

Sulla, Jeffrey L.↗

Active vibration absorber for the CSI evolutionary model - Design and experimental results

The development of control of large flexible structures technology must include practical demonstrations to aid in the understanding and characterization of controlled structures in space. To support this effort, a testbed facility has been developed to study practical implementation of new control technologies under realistic conditions. The paper discusses the design of a second order, acceleration feedback controller which acts as an active vibration absorber. This controller provides guaranteed stability margins for collocated sensor/actuator pairs in the absence of sensor/actuator dynamics and computational time delay. Experimental results in the presence of these factors are presented and discussed. The robustness of this design under model uncertainty is demonstrated.

Bruner, Anne M.↗

Frequency weighted system identification and linear quadratic controller design

Application of filters for frequency weighting of Markov parameters (pulse response functions) is described in relation to system/observer identification. The time domain identification approach recovers a model which has a pulse response weighted according to frequency. The identified model is composed of the original system and filters. The augmented system is in a form which can be used directly for frequency weighted linear quadratic controller design. Data from either single or multiple experiments can be used to recover the Markov parameters. Measured acceleration signals from a truss structure are used for system identification and the model obtained is used for frequency weighted controller design. The procedure makes the identification and controler design complementary problems.

Horta, Lucas G.↗

Linear system identification via an asymptotically stable observer

This paper presents a formulation for identification of linear multivariable systems from single or multiple sets of input-output data. The system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded eigenvalue assignment procedure. The prescribed eigenvalues for the observer may be real, complex, mixed real and complex, or zero. In this formulation, the Markov parameters of the observer are identified from input-output data. The Markov parameters of the actual system are then recovered from those of the observer, and used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples using simulated noise-free data are presented to illustrate the proposed method.

Phan, Minh↗

Identification of observer/Kalman filter Markov parameters - Theory and experiments

An algorithm to compute Markov parameters of an observer or Kalman filter from experimental input and output data is discussed. The Markov parameters can then be used for identification of a state space representation, with associated Kalman gain or observer gain, for the purpose of controller design. The algorithm is a non-recursive matrix version of two recursive algorithms developed in previous works for different purposes. The relationship between these other algorithms is developed. The new matrix formulation here gives insight into the existence and uniqueness of solutions of certain equations and gives bounds on the proper choice of observer order. It is shown that if one uses data containing noise, and seeks the fastest possible deterministic observer, the deadbeat observer, one instead obtains the Kalman filter, which is the fastest possible observer in the stochastic environment. Results are demonstrated in numerical studies and in experiments on a ten-bay truss structure.

Juang, Jer-Nan↗

Discrete-time model reduction in limited frequency ranges

A mathematical formulation for model reduction of discrete time systems such that the reduced order model represents the system in a particular frequency range is discussed. The algorithm transforms the full order system into balanced coordinates using frequency weighted discrete controllability and observability grammians. In this form a criterion is derived to guide truncation of states based on their contribution to the frequency range of interest. Minimization of the criterion is accomplished without need for numerical optimization. Balancing requires the computation of discrete frequency weighted grammians. Close form solutions for the computation of frequency weighted grammians are developed. Numerical examples are discussed to demonstrate the algorithm.

Horta, Lucas G.↗

A line-of-sight performance criterion for controller design of a proposed laboratory model

A line-of-sight performance criterion is derived for a proposed Controls Structures Interaction model, and its many uses in the control design process for fine pointing control are illustrated. A linearized line-of-sight (LOS) criterion is used for direct controller design and as a performance measure to judge different control methodologies. Numerical simulation results are shown where the three approaches: linear quadratic Gaussian theory, robust eigensystem assignment, and local velocity feedback are used for vibration control. Results indicate that the linear quadratic Gaussian controller, which incorporates a linearized LOS weighting matrix directly, yields good performance without wasting energy to control motions that have no influence on the LOS.

Lim, Kyong B.↗

Analysis and application of a velocity command motor as a reaction mass actuator

A commercially available linear stepper motor is applied as a reaction mass (RM) actuator. With the actuator operating in the (RM) relative-velocity command mode, open-loop and closed-loop testing is performed to determine operational limits. With the actuator mounted on a simple beam structure, root strain, RM acceleration, or beam acceleration is used in the feedback loop to augment the structural damping. The RM relative position is also used as feedback to ensure that the RM remains centered.

Sulla, Jeffrey L.↗

System identification in the repetition domain

Procedures for system identification using realization theory in conjunction with learning control ideas are developed. The Markov parameters of the system are identified by combining data from repeated experiments. Three approaches are discussed for identification of as many Markov parameters as sample points in the experiment. Making use of all the parameters, realization theory is then employed to determine the system order and to obtain a minimal order representation. The first two approaches are non-recursive, which in the case of noise-free data yields a one step solution. The third approach uses a recursive formulation rendered from adaptive control but modified for successive experiments. A simple example shows the numerical convergence of the identified parameters as a function of the number of experiments. The procedure presented herein is an extension of the existing Eigensystem Realization Algorithm (ERA), which has been successfully applied for system identification of large structures.

Juang, Jer-Nan↗