基于状态空间模型预测算法的四旋翼无人机飞行控制

Flight Control of Quadrotor UAVs Based on State Space Model Predictive Control

针对四旋翼无人飞行器航迹、航姿控制问题,设计了一种基于模型预测控制策略的控制器.建立控制输入为标准杆量且包含电机动态的四旋翼被控对象模型,并利用模型信息设计线性扩张状态观测器.使用该观测器对四旋翼外部阵风干扰进行估计,以观测出的干扰值实时补偿控制输出,实现有抗干扰能力的四旋翼飞行器航迹、航姿控制.最后以拉盖尔基函数表征控制量序列,减小在线滚动运算量.控制效果在半物理仿真平台上进行验证,仿真结果表明该算算法有效,运算性能可以满足实际工程需要.

We present a model predictive control strategy for trajectory-keeping and attitude stabilization of an unmanned quadrotor. We build a controlled quadrotor model which includes motor dynamics with normal remote control inputs,and then design a linear extended-state observer based on the information extracted from the model. We use the observer to estimate external gust disturbance. The estimated values are used as compensation online by adjusting control input. As a result,the capacity of resisting disturbance can be achieved in trajectory-keeping. We propose Laguerre networks to capture the future control sequence,thereby resulting in a low computational burden. The controller is validated through a hardware-in-the-loop simulation,which shows that the controller has satisfactory control and computing performance that can meet the needs of practical engineering.