Abstract: This paper studies the issue of generating optimal air-to-ground guided bomb delivery trajectories for unmanned combat aerial vehicles (UCAVs), and proposes a strategy based on the Gauss pseudospectral method (GPM) to deal with difficulties of traditional methods in processing vehicle kinematic and dynamic constraints. First, a high-fidelity 3-DOF nonlinear model of a UCAV is built which takes into consideration its aerodynamic characteristics, thrust and fuel consumption characteristics and atmospheric characteristics. Second, a fast algorithm is developed for searching the envelope of a guided bomb’s launch acceptable region (LAR), which is expressed as a final constraint in order to ensure attack accuracy. Third, GPM transforms the trajectory planning problem into a nonlinear programming problem, which can be solved using a sequential quadratic programming (SQP) algorithm. To improve computation efficiency and reduce the complexity of initial guess, a multistage iterative optimization strategy is presented. Finally, numerical examples for a minimum time-consumption trajectory as well as a minimum fuel-consumption trajectory are used to demonstrate the merits of the proposed algorithm. The results show that the algorithm can generate both feasible and optimal weapon delivery trajectories.

Key words: trajectory planning, optimal control, Gauss pseudospectral method, dynamic constraint, sequential quadratic programming, unmanned combat aerial vehicle, launch acceptable region