Organizational Unit:

Aerospace Design Group

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https://hdl.handle.net/1853/70743

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Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1134

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Publication Search Results

Now showing 1 - 10 of 50

Adaptive Control for a Microgravity Vibration Isolation System

(Georgia Institute of Technology, 2005) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I. ; Whorton, Mark S. ; Georgia Institute of Technology. School of Aerospace Engineering ; United States. National Aeronautics and Space Administration ; George C. Marshall Space Flight Center

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.
System Integration and Operation of a Research Unmanned Aerial Vehicle

(Georgia Institute of Technology, 2004-01) Johnson, Eric N. ; Schrage, Daniel P. ; Georgia Institute of Technology. School of Aerospace Engineering

The use of flight simulation tools to reduce the schedule, risk, and required amount of flight testing for complex aerospace systems is a well-recognized benefit of these approaches. However, some special challenges arise when one attempts to obtain these benefits for the development and operation of a research unmanned aerial vehicle (UAV) system. Research UAV systems are characterized by the need for continual checkout of experimental software and hardware. Also, flight testing can be further leveraged by complementing experimental results with flight-test validated simulation results for the same vehicle system. In this paper, flight simulation architectures for system design, integration, and operation of an experimental helicopter-based UAV are described. The chosen helicopter-based UAV platform (a Yamaha R-Max) is well instrumented: differential GPS, an inertial measurement unit, sonar altimetry, and a three-axis magnetometer. One or two general-purpose flight processors can be utilized. Research flight test results obtained to date, including those completed in conjunction with the DARPA Software Enabled Control program, are summarized.
Limited Authority Adaptive Flight Control for Reusable Launch Vehicles

(Georgia Institute of Technology, 2003-11) Johnson, Eric N. ; Calise, Anthony J. ; Georgia Institute of Technology. School of Aerospace Engineering

In the application of adaptive flight control, significant issues arise due to limitations in the plant inputs, such as actuator displacement limits, actuator rate limits, linear input dynamics, and time delay. A method is introduced that allows an adaptive law to be designed for the system without these input characteristics and then to be applied to the system with these characteristics, without affecting adaptation. This includes allowing correct adaptation while the plant input is saturated and allows the adaptation law to function when not actually in control of the plant. To apply the method, estimates of actuator positions must be found. However, the adaptation law can correct for errors in these estimates. Proof of boundedness of system signals is provided for a single hidden-layer perceptron neural network adaptive law. Simulation results utilizing the methods introduced for neural network adaptive control of a reusable launch vehicle are presented for nominal flight and under failure cases that require considerable adaptation.
An LMI-based Stability Analysis for Adaptive Controllers

(Georgia Institute of Technology, 2009-06) Yang, Bong-Jun ; Yucelen, Tansel ; Calise, Anthony J. ; Shin, Jong-Yeob ; Georgia Institute of Technology. School of Aerospace Engineering ; Guided Systems Technologies, Inc. ; Gulfstream Aerospace Corporation

We develop a Linear Matrix Inequality (LMI) tool for analyzing the stability and performance of adaptive controllers that employ σ−modification. The formulation involves recasting the error dynamics composed of the tracking error and the weight estimator error into a linear parameter varying form. We show how stability, convergence rate, domain of attraction, and the transient and steady state behavior of the adaptive control system can be analyzed using the developed LMI tool. It is guaranteed that less conservative estimates for the convergence rate and the size of the ultimate bound for the tracking error are obtained compared to the standard analysis in the literature.
An Adaptive Vision-based Approach to Decentralized Formation Control

(Georgia Institute of Technology, 2004-08) Sattigeri, Ramachandra J. ; Calise, Anthony J. ; Evers, Johnny H. ; Georgia Institute of Technology. School of Aerospace Engineering ; Air Force Research Laboratory (Eglin Air Force Base, Fla.). Munitions Directorate

In considering the problem of formation control in the deployment of intelligent munitions, it would be highly desirable, both from a mission and a cost perspective, to limit the information that is transmitted between vehicles in formation. In a previous paper, we proposed an adaptive output feedback approach to address this problem. Adaptive formation controllers were designed that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. In this paper, we consider a modification to the adaptive control law that enables each vehicle in a leader-follower formation to track line-of-sight (LOS) range with respect to two or more neighboring vehicles with zero steady-state error. We also propose a coordination scheme in which each vehicle tracks LOS range to up to two nearest vehicles while simultaneously navigating towards a common set of waypoints. This coordination scheme does not require a unique leader for the formation, increasing robustness of the formation. As our results show, such leaderless formations can perform maneuvers like splitting to go around obstacles, rejoining after negotiating the obstacles, and changing into line-shaped formation in order to move through narrow corridors.
Vortex Model Based Adaptive Flight Control Using Synthetic Jets

(Georgia Institute of Technology, 2009-08) Muse, Jonathan A. ; Tchieu, Andrew A. ; Kutay, Ali T. ; Chaundramohan, Rajeev ; Leonard, Anthony ; Georgia Institute of Technology. School of Aerospace Engineering ; California Institute of Technology

A simple low-order model is derived for developing flight control laws for controlling the longitudinal dynamics of an aircraft using synthetic jet type actuators. Bi-directional changes in the pitching moment over a range of angles of attack are effected by controllable, nominally-symmetric trapped vorticity concentrations on both the suction and pressure surfaces near the trailing edge. Actuation is applied on both surfaces by hybrid actuators that are each comprised of a miniature obstruction integrated with a synthetic jet actuator to manipulate and regulate the vorticity concentrations. In previous work, a simple model was derived from a reduced order vortex model that includes one explicit nonlinear state for fluid variables and can be easily coupled to the rigid body dynamics of an aircraft. This paper further simplifies this model for control design. The control design is based on an output feedback adaptive control methodology that illustrates the effectiveness of using the model for achieving flight control at a higher bandwidth than achievable with typical static actuator assumptions. A unique feature of the control design is that the control variable is a pseudo-control based on regulating a control vortex strength. Wind tunnel experiments on a unique dynamics traverse verify that tracking performance is indeed better than control designs employing standard actuator modeling assumptions.
Adaptive Guidance and Control for Hypersonic Vehicles

(Georgia Institute of Technology, 2006-05) Johnson, Eric N. ; Calise, Anthony J. ; Curry, Michael D. ; Georgia Institute of Technology. School of Aerospace Engineering

Guidance and control technology is recognized as an important aspect of the military, civil, and commercial goal of reliable, low-cost, aircraft-type operations into space. Here, several guidance and control methods are extended to enable integration into a single fully adaptive guidance and control system that offers a high degree of mission flexibility, fault tolerance, and autonomy. This paper summarizes the guidance and control system and several research issues related to use of adaptive guidance and control in reusable launch vehicles. Results that demonstrate the ability of the integrated system to plan and fly abort trajectories are also presented.
Integration of Adaptive Estimation and Adaptive Control Design for Uncertain Nonlinear Systems

(Georgia Institute of Technology, 2007-08) Sattigeri, Ramachandra J. ; Calise, Anthony J. ; Kim, Byoung Soo ; Georgia Institute of Technology. School of Aerospace Engineering ; Gyeongsang National University

This paper presents a method to integrate adaptive estimation and adaptive control designs for a class of uncertain nonlinear systems having both parametric uncertainties and unmodeled dynamics. The method is based on Lyapunov-like stability analysis of all the errors in the closed-loop system. The adaptive estimator considered is a linear, time-varying Kalman filter augmented by the output of an observer neural network. The observer neural network compensates the nominal Kalman filter for modeling errors. The estimated states are used in the construction of an adaptive control solution that is based on approximate feedback linearization augmented with the outputs of an adaptive neural network controller. The presented approach is then applied to a vision-based formation flight control problem. The objective is for a follower aircraft to maintain range from a maneuvering leader aircraft using a monocular fixed camera for passive sensing of the leader's relative motion. In the implementation, the states of the adaptive estimator are estimates of line-of-sight variables and the outputs of the observer neural network are estimates of the leader acceleration. The adaptive control solution considered is an integrated guidance and control design that includes online adaptation to unmodeled nonlinearities such as the unknown leader aircraft acceleration and parametric uncertainties in the own-aircraft aerodynamic derivatives. Simulation results using a nonlinear 6DOF simulation model of a fixed-wing UAV are presented to illustrate the feasibility and efficacy of the approach.
3D Obstacle Detection Using a Single Camera

(Georgia Institute of Technology, 2009-08) Shah, Syed Irtiza Ali ; Johnson, Eric N. ; Georgia Institute of Technology. School of Aerospace Engineering

This paper aims at detecting obstacles using a single camera in an unknown three dimensional world, for 3D motion of an unmanned air vehicle. Obstacle detection is a pre-requisite for collision-free motion of a UAV through 3D space. Most research towards vision based obstacle detection and avoidance has been done for 2D planar motion of ground robots and using active sensors like laser range finders, sonar, radar etc. Passive camera based research has mostly been done, either using stereo vision (multiple cameras) or, by developing a prior expectation map of the world and its comparison with the new image data. In this paper, an attempt has been made to find a 3D solution of the obstacle detection problem using a single camera in an unknown world. The equations developed and the simulations results presented here, show that a 3D model of the scene can be generated from 2D image information from a single camera flying through a very small arc of lateral flight around the object, without the need of capturing images from all sides as in a typical 'structures from motion' problem. The forward flight simulation results show that the depth extracted from forward motion is in fact usable for large part of the image, which is a significant contribution of this work.
Augmenting Adaptive Approach to Control of Flexible Systems

(Georgia Institute of Technology, 2004) Calise, Anthony J. ; Yang, Bong-Jun ; Craig, James I. ; Georgia Institute of Technology. School of Aerospace Engineering

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.