Showing papers presented at "American Control Conference in 2017"

Practical Methodology for the Inclusion of Nonlinear Slosh Damping in the Stability Analysis of Liquid-Propelled Space Vehicles

Abstract: One of the challenges of developing flight control systems for liquid-propelled space vehicles is ensuring stability and performance in the presence of parasitic minimally damped slosh dynamics in the liquid propellants. This can be especially difficult when the fundamental frequencies of the slosh motions are in proximity to the frequency used for vehicle control. The challenge is partially alleviated since the energy dissipation and effective damping in the slosh modes increases with amplitude. However, traditional launch vehicle control design methodology is performed with linearized systems using a fixed slosh damping corresponding to a slosh motion amplitude based on heritage values. This papers presents a method for performing the control design and analysis using damping at slosh amplitudes chosen based on the resulting limit cycle amplitude of the vehicle thrust vector system due to a control-slosh interaction under degraded phase and gain margin conditions.

Model reduction for linear differential inclusions: robustness and time-variance

Abstract: This paper deals with the problem of model reduction by moment matching for linear differential inclusions. The problem is formally formulated and the notions of momentset, perturbed moment trajectory, approximate reduced order model and robust reduced order model are introduced. Two sets of results are presented. The first part of the paper deals with robustness of the reduced order models with respect to input perturbations. Exploiting this result an enhanced model reduction scheme for linear differential equations is presented. In the second part of the paper we focus on the problem of model reduction by moment matching for time-varying systems driven by time-varying signal generators. Finally, these two sets of results are used to solve the problem of model reduction for linear differential inclusions. The results are illustrated by means of numerical examples.

Full Gradient Solution to Adaptive Hybrid Control

Abstract: This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.