The article of record as published may be found at http://dx.doi.org/10.2514/2.4229A new methodology is introduced for integrated design of guidance and control systems for autonomous vehicles (AVs). The methodology proposed borrows from the theory of gain-scheduled control and leads to an efficient procedure for the design of controllers for AVs to accurately track reference trajectories defined in an inertial reference frame. The paper illustrates the application of this procedure to the design of a tracking controller for the unmanned air vehicle Bluebird. The design phase is summarized, and the performance of the resulting controller is assessed in simulation using dynamic models of the vehicle and its sensor suite.Naval Air Systems Command under the Maritime Avionics Subsystems Technology PorgamNATO FellowshipNaval Air Systems Command under the Maritime Avionics Subsystems Technology PorgamNATO Fellowshi

This paper addresses the problem of dynamic positioning and way-point tracking of underactuated autonomous underwater vehicles (AUVs) in the presence of constant unknown ocean currents and parametric modelling uncertainty. A non-linear adaptive controller is proposed that steers an AUV along a sequence of way-points consisting of desired positions (x, y) in a inertial reference frame, followed by vehicle positioning at the final target point. The controller is first derived at the kinematic level assuming that the ocean current disturbance is known. An exponential observer for the current is then designed and convergence of the resulting closed-loop system trajectories is analysed. Finally, integrator backstepping and Lyapunov based techniques are used to extend the kinematic controller to the dynamic case and to deal with model parameter uncertainty. Simulation results with a dynamic model of an underactuated autonomous underwater shuttle for the transport of benthic labs are presented and discussed.

This paper addresses the problem of steering a group of vehicles along given spatial paths while holding a desired time-varying geometrical formation pattern. The solution to this problem, henceforth referred to as the coordinated path-following (CPF) problem, unfolds in two basic steps. First, a path-following (PF) control law is designed to drive each vehicle to its assigned path, with a nominal speed profile that may be path dependent. This is done by making each vehicle approach a virtual target that moves along the path according to a conveniently defined dynamic law. In the second step, the speeds of the virtual targets (also called coordination states) are adjusted about their nominal values so as to synchronize their positions and achieve, indirectly, vehicle coordination. In the problem formulation, it is explicitly considered that each vehicle transmits its coordination state to a subset of the other vehicles only, as determined by the communications topology adopted. It is shown that the system that is obtained by putting together the PF and coordination subsystems can be naturally viewed as either the feedback or the cascade connection of the latter two. Using this fact and recent results from nonlinear systems and graph theory, conditions are derived under which the PF and the coordination errors are driven to a neighborhood of zero in the presence of communication losses and time delays. Two different situations are considered. The first captures the case where the communication graph is alternately connected and disconnected (brief connectivity losses). The second reflects an operational scenario where the union of the communication graphs over uniform intervals of time remains connected (uniformly connected in mean). To better root the paper in a nontrivial design example, a CPF algorithm is derived for multiple underactuated autonomous underwater vehicles (AUVs). Simulation results are presented and discussed.