Inspired by the practical operability and safety of unmanned aerial vehicles (UAVs) in confined areas, this paper investigates adaptive trajectory tracking control problems in multiple six-rotor UAV systems with asymmetric time-varying output constraints and input saturation. Under model and disturbance uncertainties, six-rotor UAV systems are modeled as two non-strict-feedback systems, including attitude (inner-loop) and position (outer-loop) regulation systems. For the inner-loop design, the neural-based distributed adaptive attitude consensus control protocol is employed to realize the leader-follower consensus. Adaptive first-order sliding mode differentiators and an auxiliary dynamic system are introduced to address the “explosion of complexity” and saturation nonlinearity issues, respectively. Then, an event-triggered condition is predefined to alleviate the communication loads and reduce the number of messages to be transmitted from the controller to actuator. In addition, a class of asymmetric time-varying barrier Lyapunov functions are constructed for preventing the violation of time-varying output constraints. Accordingly, the proposed double-loop control strategies guarantee that all signals of UAV systems are semi-globally and uniformly bounded. Simulation results demonstrate that the proposed control method is effective.

受到受限区域中无人机的实际可操作性和安全性的启发，本文研究了具有非对称时变输出约束和输入饱和的六旋翼无人机系统中的自适应轨迹跟踪控制问题。在模型和扰动不确定性的影响下，将六旋翼无人机系统建模为两个非严格反馈系统，包括姿态（内环）和位置（外环）调节系统。对于内环设计，采用基于神经的分布式自适应姿态共识控制协议来实现领导者跟随共识。引入自适应一阶滑模微分器和辅助动力系统，分别解决“复杂性爆炸”和饱和非线性问题。然后，预定义了一个事件触发条件，以减轻通信负载并减少要从控制器传输到执行器的消息数量。另外，构造了一类非对称时变势垒Lyapunov函数，以防止违反时变输出约束。因此，所提出的双环控制策略保证了无人机系统的所有信号都是半全局和均匀有界的。仿真结果表明，所提出的控制方法是有效的。所提出的双环控制策略保证了无人机系统的所有信号都是半全局和均匀有界的。仿真结果表明，所提出的控制方法是有效的。所提出的双环控制策略保证了无人机系统的所有信号都是半全局和均匀有界的。仿真结果表明，所提出的控制方法是有效的。