This paper presents a review of all existing discrete methods for computing the derivatives of
computational models within a unified mathematical framework. This framework hinges on a …

This paper provides a new avenue for exploiting deep neural networks to improve physics-
based simulation. Specifically, we integrate the classic Lagrangian mechanics with a deep …

Dynamics and Optimal Control of Road Vehicles uniquely offers a unified treatment of tyre,
car and motorcycle dynamics, and the application of nonlinear optimal control to vehicle …

The paper begins with a survey of advances in state-of-the-art minimum-time simulation for
road vehicles. The techniques covered include both quasi-steady-state and transient vehicle …

High pressures play a more and more important role in modern technology. Examples are
the supercritical fluid extraction of medical drugs and dyes from biological material, the …

This paper derives the equations necessary to use state transition tensors (STTs) in a
spacecraft guidance problem. The derivation includes all necessary equations up to the …

The optimal control of a Formula One car on a three-dimensional (3D) track is studied. The
track is described by its geodesic and normal curvatures, and its relative torsion. These …

An essential need for many model-based robot control algorithms is the ability to quickly and
accurately compute partial derivatives of the equations of motion. State of the art approaches …

Many optimization methods require accurate partial derivative information in order to ensure
efficient, robust, and accurate convergence. In this paper, analytic methods are developed …

Bounded-impulse trajectory models are an important component of many spacecraft
trajectory preliminary design workflows. This paper includes discussions on practical …