Trajectory generation for autonomous unmanned aircraft using inverse dynamics

摘要

The problem addressed in this research is the in-flight generation of trajectories forautonomous unmanned aircraft, which requires a method of generating pseudo-optimaltrajectories in near-real-time, on-board the aircraft, and without external intervention.The focus of this research is the enhancement of a particular inverse dynamics directmethod that is a candidate solution to the problem. This research introduces thefollowing contributions to the method.A quaternion-based inverse dynamics model is introduced that represents allorientations without singularities, permits smooth interpolation of orientations, andgenerates more accurate controls than the previous Euler-angle model.Algorithmic modifications are introduced that: overcome singularities arising fromparameterization and discretization; combine analytic and finite difference expressionsto improve the accuracy of controls and constraints; remove roll ill-conditioning whenthe normal load factor is near zero, and extend the method to handle negative-gorientations. It is also shown in this research that quadratic interpolation improves theaccuracy and speed of constraint evaluation.The method is known to lead to a multimodal constrained nonlinear optimizationproblem. The performance of the method with four nonlinear programming algorithmswas investigated: a differential evolution algorithm was found to be capable of over99% successful convergence, to generate solutions with better optimality than the quasi-Newton and derivative-free algorithms against which it was tested, but to be up to anorder of magnitude slower than those algorithms. The effects of the degree and form ofpolynomial airspeed parameterization on optimization performance were investigated,and results were obtained that quantify the achievable optimality as a function of theparameterization degree.Overall, it was found that the method is a potentially viable method of on-board near-real-time trajectory generation for unmanned aircraft but for this potential to be realizedin practice further improvements in computational speed are desirable. Candidateoptimization strategies are identified for future research.