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Mathematical model derivation of an unmanned circulation control aerial vehicle UC^2AV

Control Theory and Technology 2020年第1期18卷 1-18页

作者： Mohammed AGHA Konstantinos KANISTRAS Matthew J.RUTHERFORD kimon p.valavanis University of Denver DenverCO80210U.S.A. University of Alabama Huntsville HuntsvilleAL35899U.S.A.

This paper presents a system identification method to derive accurate mathematical models for an unmanned circulation control aerial vehicle(UC2AV)that account for the effects of circulation control(CC)on the vehicle *** X-plane flight simulator and the CIFER system identification software are utilized to first derive simulation models to verify and validate the proposed system identification *** is followed by flight tests to derive mathematical models and stability derivatives for the aircraft with CC-on and *** tests indicate a nose down pitching moment effect induced by CC,which in turn alter the UAV trim values and *** of the two sets of mathematical models reveal that CC changes the longitudinal trim values and improves the lateral maneuverability of the *** experiments indicate an acceptable match between the derived models and UAV dynamics by calculating root mean square(RMS)error values and by quantifying the model predictive ability through calculating the Theil inequality coefficient(TIC).

关键词： Mathematical modeling control system UAV circulation control

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Neural Adaptive Dynamic Surface Control for Mismatched Uncertain Nonlinear Systems with Nonlinear Feedback Errors

Neural Adaptive Dynamic Surface Control for Mismatched Uncer...

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第36届中国控制会议

作者： Shigen Gao Hairong Dong Bin Ning Tao Tang Yidong Li kimon p.valavanis State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Computer and Information Technology Beijing Jiaotong University Department of Electrical and Computer Engineering School of Engineering and Computer ScienceUniversity of Denver

ISBN: (纸本)9781538629185

This paper addresses a new nonlinear gain feedback based neural adaptive dynamic surface control（DSC） method for a class of strict feedback nonlinear systems in the presence of uncertainties and external disturbances. Besides circumventing the problem of complexity explosion, the nonlinear gain feedback technique brings a self-regulation ability into the pioneering DSC method to improve the dynamic performance of the resulted closed-loop system. Neural networks are used to online approximating the uncertainties, the over-fitting problem occurs with small probability since the signals obtained by NNs are also handled using nonlinear gain function. It is proved rigorously by Lyapunov stability theorem that all the closed-loop signals are kept semi-globally uniformly ultimately bounded, the output tracking error and the optimal neural weight vector estimation error can all be adjusted to arbitrarily small around zero characterized by design parameters in an explicit way. Furthermore,the method proposed can be extended to the control of multiple-input-multiple-output system trivially. Comparative simulation results are presented to demonstrate the effectiveness of the proposed method.

关键词： Dynamic Surface Control Neural Adaptive Control Nonlinear Gain Feedback

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Experimental evaluation of a real-time GpU-based pose estimation system for autonomous landing of rotary wings UAVs

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Control Theory and Technology 2018年第2期16卷 145-159页

作者： Alessandro BENINI Matthew J. RUTHERFORD kimon p. valavanis DU Unmanned Systems Research Institute (DU2SRI) University of Denver (DU) Denver CO 80208 U.S.A.

This paper proposes a real-time system for pose estimation of an unmanned aerial vehicle （UAV） using parallel image processing and a fiducial marker. The system exploits the capabilities of a high-performance CpU/GpU embedded system in order to provide on-board high-frequency pose estimation enabling autonomous takeoff and landing. The system is evaluated extensively with lab and field tests using a custom quadrotor. The autonomous landing is successfully demonstrated, through experimental tests, using the proposed algorithm. The results show that the system is able to provide precise pose estimation with a framerate of at least 30fps and an image resolution of 640x480 pixels. The main advantage of the proposed approach is in the use of the GpU for image filtering and marker detection. The GpU provides an upper bound on the required computation time regardless of the complexity of the image thereby allowing for robust marker detection even in cluttered environments.

关键词： UAV Vision GpU Kalman filter

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Special issue on unmanned aerial vehicles （UAVs）

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Control Theory and Technology 2018年第2期16卷 81-81页

作者： kimon p. valavanis University of Denver Denver CO U.S.A.

Dear Colleagues： UAVs have witnessed unprecedented levels of growth during the last decade. projections and predictions suggest that during the next 5-10 years growth will continue to rapidly increase, while the spectrum of UAV utilization will be dominated by civil and public domain applications, ranging from search and rescue, emergency response, disaster management, infrastructure monitoring and protection, cartography, etc. precision agriculture, surveillance and reconnaissance,

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