This paper addresses the fixed-time leader-follower consensus problem for high-order integrator multiagent systems subject to matched external disturbances. A new cascade control structure, based on a fixed-time distributed observer, is developed to achieve the fixed-time consensus tracking control. A simulation example is included to show the efficacy and the performance of the proposed control structure with respect to different initial conditions.

The attitude control of quadrotor unmanned aerial vehicle (UAV) is investigated. The aim of this paper is to develop a continuous multivariable attitude control law, which drives the attitude tracking errors of quadrotor UAV to zero in finite time. First, a multivariable super-twisting-like algorithm (STLA) is proposed for arbitrary order integrator systems subject to matched disturbances. A discontinuous integral term is incorporated in the control law in order to compensate the disturbances. A rigorous proof of the finite time stability of the close-loop system is derived by utilizing the Lyapunov method and the homogeneous technique. Then, the implementation of the developed method in an indoor quadrotor UAV is performed. The remarkable features of the developed algorithm includes the finite time convergence, the chattering suppression and the nominal performance recovery. Finally, the efficiency of the proposed method is illustrated by numerical simulations and experimental verification.

This paper addresses the fixed-time leader-follower consensus problem for second-order multiagent systems without velocity measurement. A new continuous fixed-time distributed observer-based consensus protocol is developed to achieve consensus in a bounded finite time fully independent of initial condition. A rigorous stability proof of the multiagent systems by output feedback control is presented based on the bi-limit homogeneity and the Lyapunov technique. Finally, the efficiency of the proposed methodology is illustrated by numerical simulation.

As one of the tiniest flying objects, unmanned aerial vehicles (UAVs) are often expanded as the ``swarm'' to execute missions. In this article, we investigate the multiquadcopter and target pursuit-evasion game in the obstacles environment. For high-quality simulation of the urban environment, we propose the pursuit-evasion scenario (PES) framework to create the environment with a physics engine, which enables quadcopter agents to take actions and interact with the environment. On this basis, we construct multiagent coronal bidirectionally coordinated with target prediction network (CBC-TP Net) with a vectorized extension of multiagent deep deterministic policy gradient (MADDPG) formulation to ensure the effectiveness of the damaged ``swarm'' system in pursuit-evasion mission. Unlike traditional reinforcement learning, we design a target prediction network (TP Net) innovatively in the common framework to imitate the way of human thinking: situation prediction is always before decision-making. The experiments of the pursuit-evasion game are conducted to verify the state-of-the-art performance of the proposed strategy, both in the normal and antidamaged situations.

The finite-time attitude control of quadrotor unmanned aerial vehicles (UAVs) subject to external disturbances with unknown bound is investigated in this paper. Firstly, an adaptive multi-variable finite-time stabilizing control algorithm for second-order multi-variable systems is developed based on the improved super-twisting and the equivalent control algorithms. Furthermore, the finite-time stability conditions are derived via the Lyapunov technique. The remarkable feature of the developed algorithm is to eliminate the overestimation of the control gains without loss of the sliding motion. Then, the proposed algorithm is applied for quadrotor UAVs to solve the finite-time attitude tracking problem. Finally, a comparison of the proposed multivariable algorithm with its scalar counterpart is presented and validated by both simulation and experiment results.

This paper presents a distributed consensus observer for multi-agent systems with high-order integrator dynamics to estimate the leader state. Stability analysis is carefully studied to explore the convergence properties under undirected and directed communication, respectively. Using Lyapunov functions, fixed-time (resp. finite-time) stability is guaranteed for the undirected (resp. directed) interaction topology. Finally, simulation results are presented to demonstrate the theoretical findings.