scholarly journals Adaptive Formation Tracking Control of Directed Networked Vehicles in a Time-Varying Flowfield

2021 ◽  
pp. 1-9
Author(s):  
Yang-Yang Chen ◽  
Kaiwen Chen ◽  
Alessandro Astolfi
Keyword(s):  
Tracking Control ◽  
Time Varying ◽  
Formation Tracking

scholarly journals Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4374
Author(s):  
Jose Bernardo Martinez ◽  
Hector M. Becerra ◽  
David Gomez-Gutierrez
Keyword(s):  
Obstacle Avoidance ◽  
Tracking Control ◽  
Global Coordinate System ◽  
Avoidance Task ◽  
Time Varying ◽  
Control Laws ◽  
Formation Tracking ◽  
Control Scheme ◽  
First Time ◽  
Hierarchical Scheme

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.

scholarly journals Neural-Adaptive Finite-Time Formation Tracking Control of Multiple Nonholonomic Agents With a Time-Varying Target

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 62943-62953
Author(s):  
Kai-Bo Zhou ◽  
Xiao-Kang Wu ◽  
Ming-Feng Ge ◽  
Chang-Duo Liang ◽  
Bing-Liang Hu
Keyword(s):  
Finite Time ◽  
Tracking Control ◽  
Time Varying ◽  
Formation Tracking

Time-varying formation finite-time tracking control for multi-UAV systems under jointly connected topologies

2017 ◽  
Vol 10 (4) ◽  
pp. 478-490 ◽  
Author(s):  
Tianyi Xiong ◽  
Zhiqiang Pu ◽  
Jianqiang Yi
Keyword(s):  
Finite Time ◽  
Tracking Control ◽  
Formation Control ◽  
Time Varying ◽  
Content Type ◽  
Finite Time Stability ◽  
Control Protocol ◽  
Finite Time Convergence ◽  
Switching Topologies ◽  
Formation Tracking

Purpose The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies, where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies. Design/methodology/approach A consensus-based formation control protocol is constructed to achieve the desired formation. In this paper, the time-varying formation is specified by a piecewise continuously differentiable vector, while the finite-time convergence is guaranteed by utilizing a non-linear function. Based on the graph theory, the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation. Findings The effectiveness of the proposed protocol is verified by numerical simulations. Consequently, the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader. Originality/value This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking, finite-time convergence, and switching topologies.

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