Consensus-based cooperative control of parallel fixed-wing UAV formations via adaptive backstepping

Muslimov, Tagir; Munasypov, Rustem

doi:10.1016/j.ast.2020.106416

Cited by 75 publications

(33 citation statements)

References 50 publications

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“…The control law designed based on adaptive backstepping sliding mode control can solve the unknown uncertain problem of fixed-wing UAVs, including the uncertainty of the system itself and external disturbances [33,34]. The adaptive law is used to estimate the uncertainty of the system itself and the external disturbance.…”

Section: Adaptive Backstepping Sliding Mode Control Law Designmentioning

confidence: 99%

“…Thus, the function of θ ̇ can be rewritten as θ ̇= q + (𝑐𝑜𝑠Ф − 1)q − 𝑠𝑖𝑛Ф𝑟 = q + 𝑑 θ1 (40) Where 𝑑 θ1 is the external disturbance of this system and 𝑑 θ1 = (𝑐𝑜𝑠Ф − 1)q − 𝑠𝑖𝑛Ф𝑟. Take the derivative of both sides with respect to t: θ ̈= q̇+ 𝑑 θ1 ̇ (41) Substitute (33) Therefore, the desired state-space vector of the attitude angle control system can be defined as 𝑋 = (𝛹, 𝛹 ̇, θ, θ ̇, Ф, Ф ̇)𝑇 ∈ 𝑅 6 (47) The output vector of this system can be defined as 𝑌 = (𝛹, θ, Ф) 𝑇 ∈ 𝑅 3 (48) Letting 𝑥 1 = 𝛹, 𝑥 2 = 𝛹 ̇, 𝑥 3 = θ, 𝑥 4 = θ ̇, 𝑥 5 = Ф, 𝑥 6 = Ф ̇. The related state-space function can be obtained as where 𝐷 𝛹 is the total uncertainty of the yaw angle controller, which can be expressed as 𝐷 𝛹 = ∆𝑎 𝛹1 𝑥 2 + ∆𝑎 𝛹2 𝑈 2 + 𝑑 𝛹 (51) In the process of recursion, the sliding mode surface and adaptive law need to be introduced to determine the control effect of the controller.…”

Section: A Attitude Controller Designmentioning

confidence: 99%

See 1 more Smart Citation

Design of a Fixed-Wing UAV Controller Based on Adaptive Backstepping Sliding Mode Control Method

Bao

Guo²,

Luo

et al. 2021

IEEE Access

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Section: Adaptive Backstepping Sliding Mode Control Law Designmentioning

confidence: 99%

Section: A Attitude Controller Designmentioning

confidence: 99%

Design of a Fixed-Wing UAV Controller Based on Adaptive Backstepping Sliding Mode Control Method

Bao

Guo²,

Luo

et al. 2021

IEEE Access

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“…We can also divide the methods with regard to the type of control object and its kinematic properties. Methods can also be classified with respect to their control object, such as (i) nonholonomic [ 38 , 39 ] and (ii) holonomic, and its kinematic properties. There are also formations of homogeneous and heterogeneous objects [ 40 ].…”

Section: Introductionmentioning

confidence: 99%

Virtual Electric Dipole Field Applied to Autonomous Formation Flight Control of Unmanned Aerial Vehicles

Ambroziak

Ciężkowski

2021

Sensors

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The following paper presents a method for the use of a virtual electric dipole potential field to control a leader-follower formation of autonomous Unmanned Aerial Vehicles (UAVs). The proposed control algorithm uses a virtual electric dipole potential field to determine the desired heading for a UAV follower. This method’s greatest advantage is the ability to rapidly change the potential field function depending on the position of the independent leader. Another advantage is that it ensures formation flight safety regardless of the positions of the initial leader or follower. Moreover, it is also possible to generate additional potential fields which guarantee obstacle and vehicle collision avoidance. The considered control system can easily be adapted to vehicles with different dynamics without the need to retune heading control channel gains and parameters. The paper closely describes and presents in detail the synthesis of the control algorithm based on vector fields obtained using scalar virtual electric dipole potential fields. The proposed control system was tested and its operation was verified through simulations. Generated potential fields as well as leader-follower flight parameters have been presented and thoroughly discussed within the paper. The obtained research results validate the effectiveness of this formation flight control method as well as prove that the described algorithm improves flight formation organization and helps ensure collision-free conditions.

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“…In a multi-UAV system, the formation control, namely, to make all UAVs form a prescribed geometric shape, is one of the fundamental and active problems in this field of research (Dong et al , 2015; Lee et al , 2021; Wang et al , 2021). Owing to the complex nonlinear dynamics of the quadrotor, such as underactuated, nonlinear coupling features and environmental disturbances, the formation control for multiple quadrotor UAVs system is a challenging problem (Miao et al , 2017; Muslimov and Munasypov, 2021). Seminal work on distributed control of multiple mobile autonomous agents considering replicator-mutator dynamics was presented (Yu et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Velocity-free distributed geometric formation control for underactuated UAVs

Chen

Zhan

Huang

et al. 2021

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Purpose This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks. Design/methodology/approach A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well. Findings A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy. Originality/value This is a new innovation for multi-robot formation control method to improve assembly automation.

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Consensus-based cooperative control of parallel fixed-wing UAV formations via adaptive backstepping

Cited by 75 publications

References 50 publications

Design of a Fixed-Wing UAV Controller Based on Adaptive Backstepping Sliding Mode Control Method

Design of a Fixed-Wing UAV Controller Based on Adaptive Backstepping Sliding Mode Control Method

Virtual Electric Dipole Field Applied to Autonomous Formation Flight Control of Unmanned Aerial Vehicles

Velocity-free distributed geometric formation control for underactuated UAVs

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