Computing the distribution of trajectories from a Gaussian Process model of a dynamical system is an important challenge in utilizing such models. Motivated by the computational cost of sampling-based approaches, we consider approximations of the model’s output and trajectory distribution. We show that previous work on uncertainty propagation, focussed on discrete state-space models, incorrectly included an independence assumption between subsequent states of the predicted trajectories. Expanding these ideas to continuous ordinary differential equation models, we illustrate the implications of this assumption and propose a novel piecewise linear approximation of Gaussian Processes to mitigate them.

In this contribution, we introduce an optimal control problem for hybrid Lagrangian control systems. The dynamics of these systems and their discrete approximations are derived via a hybrid variational principle which is based on the Lagrange-d'Alembert principle for continuous Lagrangian control systems. Optimal control problems are stated in a continuous and in a numerically treatable, i.e. discrete version. For the implementation, we present a two layer approach which decouples the continuous parts of a hybrid trajectory. Additionally, this enables us to solve the optimal control problem also for multiple objectives. The approach is exemplified for a simple mechanical system.

The problem of showing that Lagrangian Coherent Structures (LCS) are useful in determining near optimal trajectories for autonomous underwater vehicles (AUVs) known as gliders is investigated. This paper extends our preliminary results in couple ways. First, the ocean current flows are modeled by 3D B-spline functions in which the input variables are latitude, longitude and time, and the output variable is the ocean current velocity in 2D. The 3D (2D and time-varying) B-spline model of the ocean current is utilized in the Nonlinear Trajectory Generation (NTG) algorithm to find the optimal trajectory of the glider. The trajectories found using the 2D and time-varying B-spline ocean flows model are compared with the trajectories from 2D B-spline model in which the time is assumed to be constant in the ocean current model. In the second part of the paper, the dynamical glider model is established and controlled by gyroscopic forces rather than the simplified kinematic glider model as in the previous work. Finally, numerical solutions of several scenarios and animations of glider trajectories are presented. The results show that the 2D and time-varying B-spline ocean model not only can make the whole trajectory generating process much easier, but also the glider can reach the same destination in a comparable time and with much less energy than it does with the previous 2D ocean current model for both the kinematic and dynamic glider models. Both of the kinematic and dynamic glider optimal trajectories, successfully generated with 2D and time varying ocean current B-spline models, are shown to correspond to LCS.