This paper proposes a novel controller framework that provides trajectory tracking for an Aerial Manipulator (AM) while ensuring the safe operation of the system under unknown bounded disturbances. The AM considered here is a 2-DOF (degrees-of-freedom) manipulator rigidly attached to a UAV. Our proposed controller structure follows the conventional inner loop PID control for attitude dynamics and an outer loop controller for tracking a reference trajectory. The outer loop control is based on the Model Predictive Control (MPC) with constraints derived using the Barrier Lyapunov Function (BLF) for the safe operation of the AM. BLF-based constraints are proposed for two objectives, viz. 1) To avoid the AM from colliding with static obstacles like a rectangular wall, and 2) To maintain the end effector of the manipulator within the desired workspace. The proposed BLF ensures that the above-mentioned objectives are satisfied even in the presence of unknown bounded disturbances. The capabilities of the proposed controller are demonstrated through high-fidelity non-linear simulations with parameters derived from a real laboratory scale AM. We compare the performance of our controller with other state-of-the-art MPC controllers for AM.
翻译:本文提出一个新的控制器框架,为空中操纵器提供轨迹跟踪,同时确保系统在未知的闭关干扰下的安全运行。这里考虑的AM是一个2-DOF(自由度)操纵器,严格地附在无人驾驶飞行器上。我们提议的控制器结构遵循常规的内环PID控制,用于姿态动态和外环环控制器,用于跟踪参考轨迹。外部环控以模型预测控制为基础,其限制来自屏障Lyapunov函数(BLF),用于AM的安全运行。基于BLF的限制提议用于两个目标,即:1)避免AM与矩形墙等静态障碍发生碰撞,和2)在理想的工作空间内保持操纵器的终端效应。拟议的BLF确保即使存在未知的受困扰动,上述目标也得到满足。拟议控制器的能力通过高不线模拟显示,其参数来自实际实验室规模的AM。我们将我们的控制器的性能与其他MAC的状态控制器作比较。