Bearing-based hunting protocols commonly adopt a leaderless consensus method,which requests an entire state of the target for each agent and ignores the necessity of collision avoidance.We investigate a hunting proble...Bearing-based hunting protocols commonly adopt a leaderless consensus method,which requests an entire state of the target for each agent and ignores the necessity of collision avoidance.We investigate a hunting problem of multi-quadrotor systems with hybrid bearing protocols,where the quadrotor systems are divided into master and slave groups for reducing the onboard loads and collision avoidance.The masters obtain the entire state of the target,whose hybrid protocols are based on the displacement and bearing constraints to maintain formation and to avoid the collision in the hunting process.However,the slaves’protocols merely depend on the part state of the masters to reduce loads of data transmission.We also investigate the feasibility of receiving the bearing state from machine vision.The simulation results are given to illustrate the effectiveness of the proposed hybrid bearing protocols.展开更多
This paper presents a graph rigidity-based formation control law for multiple quadrotors,addressing parameter uncertainties and state constraints.A Barrier Lyapunov function and a saturation function are utilized to e...This paper presents a graph rigidity-based formation control law for multiple quadrotors,addressing parameter uncertainties and state constraints.A Barrier Lyapunov function and a saturation function are utilized to enforce constraints directly on the actual states rather than on state errors.Building upon the backstepping design methodology,formation control algorithms for multi-quadrotor systems are developed,consisting of a position control loop and an attitude control loop.In the position control loop,a formation controller based on rigidity graph theory is implemented,incorporating output and state constraints to effectively manage formation flightmissions under various constrained conditions.Additionally,a Radial Basis Function(RBF) neural network is mployed to compensate for system uncertainties,enhancing robustness and stability.In the attitude control loop,an attitude tracking controller is designed to ensure accurate attitude tracking.Finally,simulations are conducted to validate the effectiveness of the proposed control strategy.展开更多
This paper investigates the flocking and obstacle avoidance problem of multi-quadrotor system with a lattice-type structure.To tackle nonlinear dynamics and cooperative consensus of a swarm of quadrotors,we proposed t...This paper investigates the flocking and obstacle avoidance problem of multi-quadrotor system with a lattice-type structure.To tackle nonlinear dynamics and cooperative consensus of a swarm of quadrotors,we proposed two algorithms(one for free flocking and one for constrained flocking)based on artificial potential field with two cooperative strategies using position tracking and attitude tracking,respectively.Firstly,the inner-loop control model of single quadrotor is provided.Then,we build an artificial potential function to act on the coordinate variable.Third,obstacle avoidance term is added to the flocking algorithm proposed previously.Finally,the position and attitude are taken as the coordinate variables,respectively,to both two algorithms,one for optimizing the distance of each quadrotor until the lattice-type structure is formed and keeping continuously and another for optimizing the distance between quadrotor and obstacles to avoid collision.Simulation results demonstrate the validity of both algorithms.展开更多
In this paper, we design consensus algorithms for multiple unmanned aerial vehicles （UAV）. We mainly focus on the control design in the face of measurement noise and propose a position consensus controller based on ...In this paper, we design consensus algorithms for multiple unmanned aerial vehicles （UAV）. We mainly focus on the control design in the face of measurement noise and propose a position consensus controller based on the sliding mode control by using the distributed UAV information. Within the framework of Lyapunov theory, it is shown that all signals in the closed-loop multi- UAV systems are stabilized by the proposed algorithm, while consensus errors are uniformly ultimately bounded. Moreover, for each local UAV, we propose a mechanism to define the trustworthiness, based on which the edge weights are tuned to eliminate negative influence from stubborn agents or agents exposed to extremely noisy measurement. Finally, we develop software for a nano UAV platform, based on which we implement our algorithms to address measurement noises in UAV flight tests. The experimental results validate the effectiveness of the proposed algorithms.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61673217 and 61673214)the National Defense Basic Scientific Research Program of China(Grant No.JCKY2019606D001)the China Scholarship Council.
文摘Bearing-based hunting protocols commonly adopt a leaderless consensus method,which requests an entire state of the target for each agent and ignores the necessity of collision avoidance.We investigate a hunting problem of multi-quadrotor systems with hybrid bearing protocols,where the quadrotor systems are divided into master and slave groups for reducing the onboard loads and collision avoidance.The masters obtain the entire state of the target,whose hybrid protocols are based on the displacement and bearing constraints to maintain formation and to avoid the collision in the hunting process.However,the slaves’protocols merely depend on the part state of the masters to reduce loads of data transmission.We also investigate the feasibility of receiving the bearing state from machine vision.The simulation results are given to illustrate the effectiveness of the proposed hybrid bearing protocols.
基金supported by the National Natural Science Foundation of China under Grant 62003233the Shanxi Provincial Basic Research Program under Grant 201901D2110831+1 种基金Shanxi Province Selects the Best Candidates to Undertake Major Science and Technology Research Project under Grant 202201090301013the State Grid Shanxi Electric Power Company Technology Project under Grant 5205M0230007
文摘This paper presents a graph rigidity-based formation control law for multiple quadrotors,addressing parameter uncertainties and state constraints.A Barrier Lyapunov function and a saturation function are utilized to enforce constraints directly on the actual states rather than on state errors.Building upon the backstepping design methodology,formation control algorithms for multi-quadrotor systems are developed,consisting of a position control loop and an attitude control loop.In the position control loop,a formation controller based on rigidity graph theory is implemented,incorporating output and state constraints to effectively manage formation flightmissions under various constrained conditions.Additionally,a Radial Basis Function(RBF) neural network is mployed to compensate for system uncertainties,enhancing robustness and stability.In the attitude control loop,an attitude tracking controller is designed to ensure accurate attitude tracking.Finally,simulations are conducted to validate the effectiveness of the proposed control strategy.
文摘This paper investigates the flocking and obstacle avoidance problem of multi-quadrotor system with a lattice-type structure.To tackle nonlinear dynamics and cooperative consensus of a swarm of quadrotors,we proposed two algorithms(one for free flocking and one for constrained flocking)based on artificial potential field with two cooperative strategies using position tracking and attitude tracking,respectively.Firstly,the inner-loop control model of single quadrotor is provided.Then,we build an artificial potential function to act on the coordinate variable.Third,obstacle avoidance term is added to the flocking algorithm proposed previously.Finally,the position and attitude are taken as the coordinate variables,respectively,to both two algorithms,one for optimizing the distance of each quadrotor until the lattice-type structure is formed and keeping continuously and another for optimizing the distance between quadrotor and obstacles to avoid collision.Simulation results demonstrate the validity of both algorithms.
基金This work was supported in part by the National Natural Science Foundation of China （No. 61633007, 61703112）, in part by the China Postdoctoral Science Foundation （No. 2016M600643） and the special fund （No. 2017T100618）, and in part by the Office of Naval Research （No. N00014-17-1-2239, NO0014-18-1-2221 ）.
文摘In this paper, we design consensus algorithms for multiple unmanned aerial vehicles （UAV）. We mainly focus on the control design in the face of measurement noise and propose a position consensus controller based on the sliding mode control by using the distributed UAV information. Within the framework of Lyapunov theory, it is shown that all signals in the closed-loop multi- UAV systems are stabilized by the proposed algorithm, while consensus errors are uniformly ultimately bounded. Moreover, for each local UAV, we propose a mechanism to define the trustworthiness, based on which the edge weights are tuned to eliminate negative influence from stubborn agents or agents exposed to extremely noisy measurement. Finally, we develop software for a nano UAV platform, based on which we implement our algorithms to address measurement noises in UAV flight tests. The experimental results validate the effectiveness of the proposed algorithms.
