基于改进高斯伪谱法的多无人机协同轨迹规划

针对当前伪谱法求解无人机轨迹存在的计算量大、运算时间长以及难以保证最优性等问题,提出了将粒子群算法与高斯伪谱法相结合的改进方法。首先,使用粒子群算法进行航迹预规划,保证近似最优解的快速实现;其次,针对高斯伪谱法配点的相对位置选取,对粒子群预规划的航迹点做拟合处理,并以此作为高斯伪谱法的初始参考指令,从而解决伪谱法的初值敏感问题,加快优化算法的收敛速度。最后,综合考虑无人机编队性能指标、飞行环境以及协同飞行约束等进行实验。实验结果验证了初值选取的重要性,同时表明了所设计算法可提升解的最优性与收敛速度。研究结果可为多无人机协同飞行控制快速规划出多维度、高精度的引导指令,对实现智能自主化飞行有一定参考价值。

Cooperative trajectory planning of multi-unmanned aerial vehicle based on improved Gauss pseudospectral method

In order to solve the problems of large computation amount, long operation time and difficulty in ensuring optima-lity, an improved method combining particle swarm optimization algorithm and Gaussian pseudospectral method was proposed. Firstly, particle swarm optimization algorithm was used for track pre-planning to ensure the fast realization of approximate optimal solution. Secondly, according to the selection of relative positions of collocation points of Gaussian pseudospectral method, the path points of pre-planned particle swarm optimization were fitted, which was used as the initial reference instruction of Gaussian pseudospectral method, so as to solve the problem of initial value sensitivity of pseudospectral method and accelerate the convergence speed of optimization algorithm. Finally, simulation experiments were carried out by taking the performance index of unmanned aerial vehicle formation, flight environment and cooperative flight constraints into consideration. Simulation results verify the importance of the selection of initial value and show that the designed algorithm could improve the optimization and convergence speed of the solution. The research results can be used to quickly plan multi-dimensional and high-precision guidance instructions for coordinated flight control of multiple UAVs, and have certain reference value for the realization of intelligent autonomous flight.