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This article addresses the high‐accuracy intelligent trajectory tracking control problem of a quadrotor unmanned aerial vehicle (UAV) subject to external disturbances. The tracking error systems are first reestablished by utilizing the feedforward control technique to compensate for the raw error dynamics of the quadrotor UAV. Then, two novel appointed‐fixed‐time observers are designed for the processed error systems to reconstruct the disturbance forces and torques, respectively. And the observation errors can converge to origin within the appointed time defined by users or designers. Subsequently, two novel control policies are developed utilizing reinforcement learning methodology, which can balance the control cost and control performance. Meanwhile, two critic neural networks are used to replace the traditional actor‐critic networks for approximating the solutions of Hamilton–Jacobi–Bellman equations. More specifically, two novel weight update laws are developed. They can not only update the weights of the critic neural networks online, but also avoid utilizing the persistent excitation condition innovatively. And that the ultimately uniformly bounded stability of the whole control system is proved according to Lyapunov method by utilizing the proposed reinforcement learning‐based control polices. Finally, simulation results are presented to illustrate the effectiveness and superior performances of the developed control scheme. [ABSTRACT FROM AUTHOR]

Single UAVs have limited capabilities for complex missions, so suitable solutions are needed to improve the mission success rate, as well as the UAVs' survivability. A cooperative multi-UAV formation offers great advantages in this regard; however, for large and complex systems, the traditional control methods will be invalid when faced with unstable and changing environments. To deal with the poor self-adaptability and high requirements for the environmental state information of traditional control methods for a multi-UAV cluster, this paper proposes a consistent round-up strategy based on PPO path optimization to track targets. In this strategy, the leader is trained using PPO for obstacle avoidance and target tracking, while the followers are expected to establish a communication network with the leader to obtain environmental information. In this way, the tracking control law can be designed, based on the consistency protocol and the Apollonian circle, to realize the round-up of the target and obstacle avoidance. The experimental results show that the proposed strategy can achieve the round-up of the target UAV and guide the pursuing multi-UAV group to avoid obstacles in the absence of the initial detection of the target. In multiple simulated scenarios, the success rates of the pursuit multi-UAV cluster for rounding up the target are maintained above 80%. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of trajectory tracking control for quadrotor unmanned aerial vehicle (UAV) in the presence of dynamic obstacles and external disturbance forces/torques. More specifically, two new sliding mode disturbance observers are firstly designed to estimate the external disturbances, in which the observation errors can converge to zero in finite time. Furthermore, utilizing the observation information, a new sliding mode surface‐like variable‐based position tracking control scheme and a novel nonsingular terminal sliding mode‐based attitude synchronization control scheme are developed to drive the UAV tracking the reference trajectory with obstacle avoiding. Moreover, the tracking errors of the close‐loop control system can converge to zero within finite time by the analyses of Lyapunov methodology. Finally, the numerical simulation results are presented to illustrate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

The problem of simultaneous estimation of states and uncertainties by using limited information is investigated in this article. A sampled‐data learning observer (SLO) is presented for linear time‐invariant continuous systems, which can achieve successful estimation while only needs intermittent sampled‐data, saves computing resources, and does not require persistent excitation signals. The observer's demand for continuous measurement is reduced, that is, limited‐information is sufficient. Notably, the uncertainty estimation is performed by a learning equation with only simple addition operations, which is particularly suitable for actual digital system scenarios. Simulation results illustrate the effectiveness of the proposed SLO. [ABSTRACT FROM AUTHOR]

An adaptive fuzzy second-order terminal sliding mode control scheme is developed to solve the problem of rigid spacecraft attitude maneuver in which the external disturbances and uncertain inertia parameters as well as actuator faults are explicitly taken into account. The proposed controller incorporates a second-order terminal sliding mode to obtain finite time convergent performance as well as chattering elimination, meanwhile the fuzzy logical system is implemented to estimate the system uncertainties of the rigid spacecraft. Lyapunov stability analysis shows that the designed control algorithm guarantees the practical finite time stability of the attitude maneuver errors with great robustness to system uncertainties and actuator faults. Numerical simulations are also presented that not only highlights closed-loop performance benefits from the proposed control algorithm, but also illustrates its effectiveness in the presence of disturbances and uncertainties when compared with classic finite time sliding mode control schemes for spacecraft attitude maneuver control. [ABSTRACT FROM AUTHOR]

To solve the rigid spacecraft attitude maneuver problem, an adaptive fuzzy fault-tolerant sliding mode controller is designed. The controller is based on the terminal sliding mode scheme. The adaptive learning algorithm and the fuzzy logic system are designed to estimate the attitude tracking dynamics. The stability of the controller is proved by Lyapunov method. Finite-time convergence of spacecraft attitude orientation to the neighborhood of the equilibrium point is obtained. Finally, a numerical simulation is employed to illustrate the advantages of the proposed controller. Simulation results confirm that the designed controller yields high control precision and great fault-tolerant capability. [ABSTRACT FROM AUTHOR]