Adaptive feedback linearizing nonlinear close formation control of UAVs

Singh, Sahjendra N.; Chandler, P.; Schumacher, Corey; Banda, Siva S.; Pachter, Meir

doi:10.1109/acc.2000.876620

Cited by 46 publications

(35 citation statements)

References 7 publications

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“…Zong [10] tried to solve the coordinative optimization problems among every individual UAV with flexible and smart ways by interactive communications and information feedback in multi-agent system (MAS) so as to implement the autonomous formation flight of multi-UAVs. In addition, many other control approaches have been introduced to the research of the multi-UAVs close formation, such as nonlinear adaptive control [11], fuzzy logic [12], and robust control [13].…”

Section: Introductionmentioning

confidence: 99%

Receding horizon control for multi-UAVs close formation control based on differential evolution

Zhang¹,

Duan²,

Yuan³

2010

Sci. China Inf. Sci.

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Close formation flight is one of the most complicated problems on multi-uninhabited aerial vehicles (UAVs) coordinated control. Based on the nonlinear model of multi-UAVs close formation, a novel type of control strategy of using hybrid receding horizon control (RHC) and differential evolution algorithm is proposed. The issue of multi-UAVs close formation is transformed into several on-line optimization problems at a series of receding horizons, while the differential evolution algorithm is adopted to optimize control sequences at each receding horizon. Then, based on the Markov chain model, the convergence of differential evolution is proved. The working process of RHC controller is presented in detail, and the stability of close formation controller is also analyzed. Finally, three simulation experiments are performed, and the simulation results show the feasibility and validity of our proposed control algorithm.

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Section: Introductionmentioning

confidence: 99%

Receding horizon control for multi-UAVs close formation control based on differential evolution

Zhang¹,

Duan²,

Yuan³

2010

Sci. China Inf. Sci.

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“…Inertial trajectory control is essential for these UAVs, since they are usually required to follow predetermined paths through certain target points in the threedimensional air space [29,96,97,151,171,172,184]. Other situations where trajectory control is desired include formation control, aerial refueling and autonomous landing maneuvers [68,155,156,168,182,207]. This has lead to a lot of literature dedicated to formation and flight path control for UAVs, but also for other types of (un)manned vehicles [80,146].…”

Section: Motivationmentioning

confidence: 99%

Adaptive Backstepping Flight Control for Modern Fighter Aircraft

Sonneveldt¹

2011

Advances in Flight Control Systems

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“…For instance, there has been a growing interest in groups (swarms) of flying vehicles [9]. It has been argued that a swarm of robots can accomplish some tasks that would be impossible for a single robot to achieve.…”

Section: Introductionmentioning

confidence: 99%

Stability analysis of one-dimensional asynchronous swarms

Liu

Passino

Polycarpou

2001

Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148)

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Abstract-Coordinated swarm behavior in certain types of animals can also occur in groups of autonomous vehicles. Swarm "cohesiveness" is characterized as a stability property. Conditions for one-dimensional asynchronous swarms to achieve collision-free convergence even in the presence of sensing delays and asynchronism during movements are provided. Each finite-size swarm member has proximity sensors and neighbor position sensors that only provide delayed position information. Such stability analysis is of fundamental importance if one wants to understand the coordination mechanisms for "platoons" of autonomous vehicles, where intermember communication channels are less than perfect and collisions must be avoided.

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Adaptive feedback linearizing nonlinear close formation control of UAVs

Cited by 46 publications

References 7 publications

Receding horizon control for multi-UAVs close formation control based on differential evolution

Receding horizon control for multi-UAVs close formation control based on differential evolution

Adaptive Backstepping Flight Control for Modern Fighter Aircraft

Stability analysis of one-dimensional asynchronous swarms

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