基于控制向量参数化和迭代凸规划的无人机编队飞行的建立

Establishment of UAV Formation Flight Using Control Vector Parameterization and Sequential Convex Programming

多个无人机组成的编队飞行可以作为很多应用中现有技术的一种高效、低成本的替代方案。研究了能满足最终编队队形约束的且能量最优的无人机编队飞行的建立。首先,将编队建立问题建模成一个受非线性动力学约束的能量最优控制问题。其次,采用直接法来求解该最优控制问题。在采用的直接法中,利用控制向量参数化方法将原始问题转化成一系列待求解的凸优化问题;然后,运用迭代凸规划(SCP)技术求得其最优解。在求解过程中,SCP迭代的每一步本质上都是一个二次型规划问题;由于该规划问题的约束是线性约束,因此可以高效地进行求解。最后,将提出的方法运用到3个无人机的V型编队建立中,并使用了免费的开源求解器CVX进行求解。与MATLAB中提供的全局优化技术相比,文中提出的算法能够快速地收敛到全局最小值。

Formation flight of multiple Unmanned Aerial Vehicles （ UAVs） could provide an effective, efficient yet cost reduction alternative to existing technologies of various applications. This paper addresses the energy-optimal establishment of UAV formation flight that shall satisfy final configuration constraints. First, the problem of formation establishment is formulated as an energy-optimal control problem which is subject to the nonlinear dy-namics constraints. Then, the optimal control problem is solved using a direct method. In this direct method the o-riginal problem is transcribed into a sequence of convex optimization problems via the control vector parameterization approach. After that, the sequential convex programming （ SCP ） technology is employed to derive the optimal solution. Essentially, each instance of SCP is a quadratic programming problem subject to linear con-straints that can be solved very efficiently. In the end, the proposed method is applied to the establishment of V for-mation for three UAVs, where the free open source CVX is exploited. By comparison with the global optimization technique provided in MATLAB, the solution converges very fast to the global minimum.