摘要
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。
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.
出处
《电光与控制》
北大核心
2013年第1期9-13,48,共6页
Electronics Optics & Control
基金
航空科学基金项目(20110184001)
关键词
无人机
视觉编队
飞行控制
预测控制
加速度估计
unmanned aerial vehicle
vision-based formation
flight control
model predictive control
acceleration estimation
