experimental cooperative control of fixed wing unmanned aerial vehicles

• DOI: 10.1109/CDC.2004.1429426
• Corpus ID: 694554

Experimental cooperative control of fixed-wing unmanned aerial vehicles

• S. Bayraktar , Georgios Fainekos , George Pappas
• Published in IEEE Conference on Decision… 1 December 2004
• Computer Science, Engineering

105 Citations

Hybrid modeling and experimental cooperative control of multiple unmanned aerial vehicles, coordinated control of multiple uavs : theory and flight experiment, developments in hybrid modeling and control of unmanned aerial vehicles, flight modeling and experimental autonomous hover control of a fixed wing mini-uav at high angle of attack, development of a fixed wing multi-role unmanned aircraft vehicle research testbed, control of multi-agent collaborative fixed-wing uass in unstructured environment, coordinated flight control of miniature fixed-wing uav swarms: methods and experiments, characterization of uav performance and development of a formation flight controller for multiple small uavs, decentralized mesh-based model predictive control for swarms of uavs, nonlinear maneuvering control of rigid formations of fixed wing uavs, 27 references, autonomous vehicle technologies for small fixed-wing uavs, on controlling aircraft formations, lateral track control law for aerosonde uav, flying robots: modeling, control and decision making, the georgia tech unmanned aerial research vehicle: gtmax, uav and ugv collaboration for active ground feature search and localization, decentralized cooperative trajectory planning of multiple aircraft with hard safety guarantees, dragonfly: a versatile uav platform for the advancement of aircraft navigation and control, strategies of path-planning for a uav to track a ground vehicle, related papers.

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Experimental cooperative control of fixed-wing unmanned aerial vehicles

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Experimental cooperative control of fixed-wing unmanned aerial vehicles

Research output : Chapter in Book/Report/Conference proceeding › Conference contribution

Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

Publication series

ASJC Scopus subject areas

• Control and Systems Engineering
• Modeling and Simulation
• Control and Optimization

Access to Document

• 10.1109/CDC.2004.1429426

Other files and links

• Link to publication in Scopus

Fingerprint

• Unmanned Aerial Vehicle Engineering 100%
• Fixed Wings Engineering 100%
• Cooperative Control Engineering 100%
• Fixed-wing Unmanned Aerial Vehicles Keyphrases 100%
• Physical Dynamic Computer Science 50%
• Whigs Keyphrases 33%
• Fixed-wing UAV Keyphrases 33%
• Collaborative Sensing Keyphrases 33%

T1 - Experimental cooperative control of fixed-wing unmanned aerial vehicles

AU - Bayraktar, Selcuk

AU - Fainekos, Georgios E.

AU - Pappas, George J.

N1 - Funding Information: The National Natural Science Foundation of China (Nos. 51278299 and 51478264) supported this work. Rui Sun and Renjie Luo took part in conducting summer experiments and did some preliminary analysis.

N2 - Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

AB - Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

UR - http://www.scopus.com/inward/record.url?scp=14244252724&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=14244252724&partnerID=8YFLogxK

U2 - 10.1109/CDC.2004.1429426

DO - 10.1109/CDC.2004.1429426

M3 - Conference contribution

AN - SCOPUS:14244252724

SN - 0780386825

T3 - Proceedings of the IEEE Conference on Decision and Control

BT - 2004 43rd IEEE Conference on Decision and Control (CDC)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2004 43rd IEEE Conference on Decision and Control (CDC)

Y2 - 14 December 2004 through 17 December 2004

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Computer Science > Systems and Control

Title: collaborative target-tracking control using multiple autonomous fixed-wing uavs with constant speeds.

Abstract: This paper considers a collaborative tracking control problem using a group of fixed-wing unmanned aerial vehicles (UAVs) with constant and non-identical speeds. The dynamics of fixed-wing UAVs are modelled by unicycle-type equations with nonholonomic constraints, assuming that UAVs fly at constant altitudes in the nominal operation mode. The controller is designed such that all fixed-wing UAVs as a group can collaboratively track a desired target's position and velocity. We first present conditions on the relative speeds of tracking UAVs and the target to ensure that the tracking objective can be achieved when UAVs are subject to constant speed constraints. We construct a reference velocity that includes both the target's velocity and position as feedback, which is to be tracked by the group centroid. In this way, all vehicles' headings are controlled such that the group centroid follows a reference trajectory that successfully tracks the target's trajectory. A spacing controller is further devised to ensure that all vehicles stay close to the group centroid trajectory. Trade-offs in the controller design and performance limitations of the target tracking control due to the constant-speed constraint are also discussed in detail. Experimental results with three fixed-wing UAVs tracking a target rotorcraft are provided.

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A control system design and implementation for autonomous quadrotors with real-time re-planning capability.

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Share and Cite

Kovryzhenko, Y.; Li, N.; Taheri, E. A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability. Robotics 2024 , 13 , 136. https://doi.org/10.3390/robotics13090136

Kovryzhenko Y, Li N, Taheri E. A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability. Robotics . 2024; 13(9):136. https://doi.org/10.3390/robotics13090136

Kovryzhenko, Yevhenii, Nan Li, and Ehsan Taheri. 2024. "A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability" Robotics 13, no. 9: 136. https://doi.org/10.3390/robotics13090136

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Experimental cooperative control of fixed-wing unmanned aerial vehicles

Research output : Chapter in Book/Report/Conference proceeding › Conference contribution

Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

Publication series

ASJC Scopus subject areas

• Control and Systems Engineering
• Modeling and Simulation
• Control and Optimization

Access to Document

• 10.1109/CDC.2004.1429426

Other files and links

• Link to publication in Scopus
• Link to the citations in Scopus

Fingerprint

• Unmanned Aerial Vehicle Engineering 100%
• Fixed Wings Engineering 100%
• Cooperative Control Engineering 100%
• Physical Dynamic Computer Science 50%
• Whigs Keyphrases 33%
• Fixed-wing UAV Keyphrases 33%
• Aerial Sensor Networks Keyphrases 33%
• Control Experiment Engineering 25%

T1 - Experimental cooperative control of fixed-wing unmanned aerial vehicles

AU - Bayraktar, Selcuk

AU - Fainekos, Georgios E.

AU - Pappas, George J.

N1 - Funding Information: The National Natural Science Foundation of China (Nos. 51278299 and 51478264) supported this work. Rui Sun and Renjie Luo took part in conducting summer experiments and did some preliminary analysis.

N2 - Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

AB - Recent years have seen rapidly growing interest in the development of networks of multiple unmanned aerial vehicles (U.A.V.s), as aerial sensor networks for the purpose of coordinated monitoring, surveillance, and rapid emergency response. This has triggered a great deal of research in higher levels of planning and control, including collaborative sensing and exploration, synchronized motion planning, and formation or cooperative control. In this paper, we describe our recently developed experimental testbed at the University of Pennsylvania, which consists of multiple, fixed-whig UAVs. We describe the system architecture, software and hardware components, and overall system integration. We then derive high-fidelity models that are validated with hardware-in-the-loop simulations and actual experiments. Our models are hybrid, capturing not only the physical dynamics of the aircraft, but also the mode switching logic that supervises lower level controllers. We conclude with a description of cooperative control experiments involving two fixed-wing UAVs.

UR - http://www.scopus.com/inward/record.url?scp=14244252724&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=14244252724&partnerID=8YFLogxK

U2 - 10.1109/CDC.2004.1429426

DO - 10.1109/CDC.2004.1429426

M3 - Conference contribution

SN - 0780386825

T3 - Proceedings of the IEEE Conference on Decision and Control

BT - 2004 43rd IEEE Conference on Decision and Control (CDC)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2004 43rd IEEE Conference on Decision and Control (CDC)

Y2 - 14 December 2004 through 17 December 2004

Event-Triggered Adaptive Fixed-Time Trajectory Tracking Control for Stratospheric Airship

• Original Paper
• Published: 10 September 2024

Cite this article

• Peihao Sun 1 ,
• Ming Zhu 2 ,
• Yifei Zhang   ORCID: orcid.org/0009-0002-9565-2046 2 ,
• Tian Chen 2 &
• Zeiwei Zheng 3  

This paper proposes a trajectory tracking controller to address the issue of the unmeasurable airspeed of a stratospheric airship. First, we propose a fixed-time extended state observer in solving the issues of unknown disturbances and unmeasurable airspeed. Utilizing the sliding mode control and backstepping framework, a fixed-time convergent controller is designed in this paper. Then, the fixed-time controller is integrated with the event-triggered mechanism to decrease the actuation frequency of the actuator during the tracking of the predetermined trajectory. After that, we provide a proof that the observer error converges to zero within a fixed time and the semi-global fixed-time uniform ultimate boundedness of the closed-loop output feedback control system is proved by Lyapunov stability analysis. The simulation results validate the efficacy of the algorithm.

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Basin M, Yu P, Shtessel Y (2017) Finite-and fixed-time differentiators utilising HOSM techniques. IET Control Theory Appl 11(8):1144–1152

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This work was supported by the National Natural Science Foundation of China (Grant No. 52402509, Grant No. 62173016), and the the Fundamental Research Funds for the Central Universities (Grant No. 501JCGG2024129007, Grant No. 501JCGG2024103002).

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School of Aeronautic Science and Engineering, Beihang University, Beijing, China

Institute of Unmanned System, Beihang University, Beijing, China

Ming Zhu, Yifei Zhang & Tian Chen

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Conceptualization, P.S. and Y.Z.; methodology, P.S.; software, P.S.; validation, P.S. and Y.Z.; formal analysis, P.S.; investigation, P.S.; resources, P.S.; data curation, P.S.; writing–original draft preparation, P.S.; writing?review and editing, Y.Z. and T.C.; visualization, P.S.; supervision, M.Z., T.C. and Z.Z.; project administration, M.Z. and Z.Z. All authors have read and agreed to the published version of the manuscript.

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Sun, P., Zhu, M., Zhang, Y. et al. Event-Triggered Adaptive Fixed-Time Trajectory Tracking Control for Stratospheric Airship. Int. J. Aeronaut. Space Sci. (2024). https://doi.org/10.1007/s42405-024-00816-3

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Received : 19 April 2024

Revised : 12 August 2024

Accepted : 20 August 2024

Published : 10 September 2024

DOI : https://doi.org/10.1007/s42405-024-00816-3

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