基于预测控制方法的UAV视觉编队飞行控制律设计

传统的无人飞行器(UAV)视觉编队控制律考虑约束的能力不足,制约了其工程实际应用。针对不足,基于预测控制方法设计了一种能够显式考虑约束的视觉编队控制律,该控制律通过滚动求解有限时域优化问题得到跟随飞行器(follower)的控制输入。利用相对距离变化率和视线方位角变化率预测值与实测值的偏差信息,提出了领航飞行器(leader)加速度的在线估计算法。仿真结果表明,所设计的编队控制律能够控制follower飞行器快速跟随leader飞行器形成期望的编队,所提出的leader飞行器加速度估计方法可行,具有较小的估计误差。

Vision-Based UAV Formation Control Law Design Based on Model Predictive Control Method

Traditional vision-based UAV formation control law have less capability of considering constraints.A new formation control law which can explicitly consider constraints on states and control inputs was designed for vision-based formation flight based on Model Predictive Control (MPC).Control inputs of the follower UAV at each sampling instant were obtained by solving a finite horizon optimization control problem.To estimate the acceleration of the leader UAV an estimation algorithm was proposed based on the difference between predicted states and measured states in the framework of MPC.Simulation results show that the designed formation control law can drive UAVs to achieve the prescribed formation quickly and maintain the configuration in the presence of leader maneuvers.The proposed acceleration estimation algorithm is effective and has low estimation error.