Organizational Unit:
Aerospace Design Group
Aerospace Design Group
Permanent Link
Research Organization Registry ID
Description
Previous Names
Parent Organization
Parent Organization
Organizational Unit
Includes Organization(s)
ArchiveSpace Name Record
Publication Search Results
Now showing
1 - 8 of 8
-
ItemAdaptive, Integrated Guidance and Control Design for Line-of-Sight-Based Formation Flight(Georgia Institute of Technology, 2007-10) Kim, Byoung Soo ; Calise, Anthony J. ; Sattigeri, Ramachandra J.This paper presents an integrated guidance and control design for formation flight using a combination of adaptive output feedback and backstepping techniques. We formulate the problem as an adaptive output feedback control problem for a line-of-sight-based formation flight configuration of a leader and a follower aircraft. The design objective is to regulate range and two bearing angle rates while maintaining turn coordination. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process. These include uncertainties due to unknown leader aircraft acceleration, and the modeling error due to parametric uncertainties in the aircraft aerodynamic derivatives. One benefit of this approach is that the guidance and flight control design process is integrated. Simulation results using a nonlinear 6 degrees-of-freedom simulation model are presented to illustrate the efficacy of the approach by comparing the performance with an adaptive timescale separation-based guidance and control design.
-
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.
-
ItemReal-Time Vision-Based Relative Aircraft Navigation(Georgia Institute of Technology, 2007-03) Johnson, Eric N. ; Calise, Anthony J. ; Watanabe, Yoko ; Ha, Jin-Cheol ; Neidhoefer, James C.This paper describes two vision-based techniques for the navigation of an aircraft relative to an airborne target using only information from a single camera fixed to the aircraft. These techniques are motivated by problems such as "see and avoid", pursuit, formation flying, and in-air refueling. By applying an Extended Kalman Filter for relative state estimation, both the velocity and position of the aircraft relative to the target can be estimated. While relative states such as bearing can be estimated fairly easily, estimating the range to the target is more difficult because it requires achieving valid depth perception with a single camera. The two techniques presented here offer distinct solutions to this problem. The first technique, Center Only Relative State Estimation, uses optimal control to generate an optimal (sinusoidal) trajectory to a desired location relative to the target that results in accurate range-to-target estimates while making minimal demands on the image processing system.The second technique, Subtended Angle Relative State Estimation, uses more rigorous image processing to arrive at a valid range estimate without requiring the aircraft to follow a prescribed path. Simulation results indicate that both methods yield range estimates of comparable accuracy while placing different demands on the aircraft and its systems.
-
ItemAdaptive Guidance and Control for Hypersonic Vehicles(Georgia Institute of Technology, 2006-05) Johnson, Eric N. ; Calise, Anthony J. ; Curry, Michael D.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.
-
ItemNeural-Network Augmentation of Existing Linear Controllers(Georgia Institute of Technology, 2005-01) Sharma, Manu ; Calise, Anthony J.A method to augment existing linear controllers with a multilayer neural network is presented. The neural network is adapted online to ensure desired closed-loop response in the face of parametric plant uncertainty; no off-line training is required. The benefit of this scheme is that the neural-network output is simply added to the nominal control signal, thereby preserving the existing control architecture. Furthermore, the nominal control signal is only modified if the desired closed-loop response is not met. This method applies to a large class of modern and classical linear controllers. Stability guarantees are provided via Lyapunov-like analysis, and the efficacy of this scheme is illustrated through two numerical examples.
-
ItemAn Adaptive Vision-Based Approach to Decentralized Formation Control(Georgia Institute of Technology, 2004-12) Sattigeri, Ramachandra J. ; Calise, Anthony J. ; Evers, Johnny H.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. We have proposed an adaptive output feedback approach to address this problem. Adaptive formation controllers are designed that allow each vehicle in formation to maintain separation and relative orientation with respect to neighboring vehicles, while avoiding obstacles. We have implemented two approaches for formation control, namely, leader-follower formations and leaderless formations. In leader-follower formations, there is a unique leader and all the other vehicles are followers. In leaderless formations, there is no unique leader. Each vehicle tracks line-of-sight range to up to two nearest vehicles while simultaneously navigating towards a common set of waypoints. 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.
-
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.
-
ItemLimited Authority Adaptive Flight Control for Reusable Launch Vehicles(Georgia Institute of Technology, 2003-11) Johnson, Eric N. ; Calise, Anthony J.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.