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Aerospace Design Group
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ItemAdaptive Output Feedback Control of a Flexible Base Manipulator(Georgia Institute of Technology, 2007-07) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I.This paper considers augmentation of an existing inertial damping mechanism by neural network-based adaptive control, for controlling a micromanipulator that is serially attached to a macromanipulator. The approach is demonstrated using an experimental test bed in which the micromanipulator is mounted at the tip of a cantilevered beam that resembles a macromanipulator with its joint locked. The inertial damping control combines acceleration feedback with position control for the micromanipulator so as to simultaneously suppress vibrations caused by the flexible beam while achieving precise tip positioning. Neural network-based adaptive elements are employed to augment the inertial damping controller when the existing control system becomes deficient due to modeling errors and uncertain operating conditions. There were several design challenges that had to be faced from an adaptive control perspective. One challenge was the presence of a nonminimum phase zero in an output feedback adaptive control design setting in which the regulated output variable has zero relative degree. Other challenges included flexibility in the actuation devices, lack of control degrees of freedom, and high dimensionality of the system dynamics. In this paper we describe how we overcame these difficulties by modifying a previous augmenting adaptive approach to make it suitable for this application. Experimental results are provided to illustrate the effectiveness of the augmenting approach to adaptive output feedback control design.
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ItemAdaptive Control of Evolving Gossamer Structures(Georgia Institute of Technology, 2006-08) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I. ; Whorton, Mark S.A solar sail is an example of a gossamer structure that is proposed as an propulsion system for future space missions. Since it is a large scale flexible structure that requires a long time for its deployment, active control may be required to prevent it from deviating into a non-recoverable state. In this paper, we conceptually address control of an evolving flexible structure using a growing double pendulum model. Controlling an evolving system poses a major challenge to control design because it involves time-varying parameters, such as inertia and stiffness. By employing a neural network based adaptive control, we illustrate that the evolving double pendulum can be effectively regulated when fixed-gain controllers are deficient due to presence of time-varying parameters.
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ItemAdaptive Control for a Microgravity Vibration Isolation System(Georgia Institute of Technology, 2005-08) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I. ; Whorton, Mark S.Most active vibration isolation systems that try to a provide quiescent acceleration environment for space-science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that combines a high-gain acceleration inner-loop feedback together with a low-gain position outer-loop feedback to regulate the platform about its center position. The control design considers both parametric and dynamic uncertainties because the isolation system must accommodate a variety of payloads having different inertial and dynamic characteristics. An important aspect of the design is the accelerometer bias. Two neural networks are incorporated to adaptively compensate for the uncertainties within the acceleration and the position loop. A novel feature in the design is that high-band pass and low pass filters are applied to the error signal used to adapt the weights in the neural network and the adaptive signals, so that the adaptive processes operate over targeted ranges of frequency. This prevents the inner and outer loop adaptive processes from interfering with each other. Simulations show that adaptive augmentation improves the performance of the existing acceleration controller and at the same time reduces the maximal position deviation and thus also improves the position controller.
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ItemAdaptive Control for a Microgravity Vibration Isolation System(Georgia Institute of Technology, 2005) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I. ; Whorton, Mark S.Most active vibration isolation systems that try to a provide quiescent acceleration environment for space-science experiments have utilized linear design methods. In this report, we address adaptive control augmentation of an existing classical controller that combines a high-gain acceleration inner-loop feedback together with a low-gain position outer-loop feedback to regulate the platform about its center position. The control design considers both parametric and dynamic uncertainties because the isolation system must accommodate a variety of payloads having different inertial and dynamic characteristics. We show how adaptive control is beneficial in three important aspects in design of a controller for uncertain systems: performance, robustness, and transient responses. First, performance is treated in the setting that an accelerometer and an actuator is located at the same location, as is the current hardware configuration for g-LIMIT. Second, robustness for the control system becomes more of an issue when the sensor is non-collocated with the actuator. We illustrate that adaptive control can stabilize otherwise unstable dynamics due to the presence of unmodelled dynamics. Third, transient responses of the position of the isolation system are significantly influenced by a high-gain acceleration controller when it includes integral action. An important aspect of the g-LIMIT is the accelerometer bias and the deviation of the platform it causes as a result of integral control. By employing adaptive neural networks for both the inner-loop and outer-loop controllers, we illustrate that adaptive control can improve both steady-state responses and transient responses in position. A feature in the design is that high-band pass and low pass filters are applied to the error signal used to adapt the weights in the neural network and the adaptive signals, so that the adaptive processes operate over targeted ranges of frequency. This prevents the inner and outer loop adaptive processes from interfering with each other.
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ItemAugmenting Adaptive Approach to Control of Flexible Systems(Georgia Institute of Technology, 2004) Calise, Anthony J. ; Yang, Bong-Jun ; Craig, James I.This paper describes an approach for augmenting a linear controller design with a neural-network-based adaptive element. The basic approach involves formulating an architecture for which the associated error equations have a form suitable for applying existing results for adaptive output feedback control of nonlinear systems. The approach is applicable to non-affine, nonlinear systems with both parametric uncertainties and unmodelled dynamics. The effect of actuator limits are treated using control hedging. The approach is particularly well suited for control of flexible systems subject to limits in control authority. Its effectiveness is tested on a laboratory experiment consisting of a three-disk torsional pendulum system, including control voltage saturation and stiction.
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ItemExperimental Validation of an Augmenting Approach to Adaptive Control of Uncertain Nonlinear Systems(Georgia Institute of Technology, 2003-08) Yang, Bong-Jun ; Hovakimyan, Naira ; Calise, Anthony J. ; Craig, James I.A method of adaptive output feedback design for uncertain nonlinear systems is presented. The development is in a form that is suitable for augmenting a linear controller. The approach is applicable to non-affine, non-minimum phase systems having parametric and dynamic uncertainties. A requirement is that the non-minimum phase zeros are represented to a sufficient accuracy in the linear controller design. The approach has been experimentally validated using a 3-disk torsional pendulum and an inverted pendulum.
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ItemAdaptive output feedback control with input saturation(Georgia Institute of Technology, 2003-06) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I.We consider the problem of adaptive output feedback control in the presence of saturating input characteristic. The adaptive control architecture augments an existing linear control design. The approach is applicable to non-affine, nonlinear systems with both parametric uncertainty and unmodeled dynamics subject to input saturation. Boundedness of signals is shown through Lyapunov's direct method. Experimental results with a 3-disk torsional pendulum are presented to demonstrate the approach.