State feedback policies for robust receding horizon control: uniqueness, continuity, and stability

Published versio

Model predictive control application to spacecraft rendezvous in mars sample return scenario

Model Predictive Control (MPC) is an optimization-based control strategy that is considered extremely attractive in the autonomous space rendezvous scenarios. The Online Recon¦guration Control System and Avionics Architecture (ORCSAT) study addresses its applicability in Mars Sample Return (MSR) mission, including the implementation of the developed solution in a space representative avionic architecture system. With respect to a classical control solution High-integrity Autonomous RendezVous and Docking control system (HARVD), MPC allows a signi¦cant performance improvement both in trajectory and in propellant save. Furthermore, thanks to the online optimization, it allows to identify improvements in other areas (i. e., at mission de¦nition level) that could not be known a priori

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This paper includes a review of established methods of inverse simulation,giving some emphasis to iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach which is based on feedback principles. This feedback method is suitable for a wide range of linear and nonlinear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model and, in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on nonlinear and multi-input multi-output models

Distributed predictive control with minimization of mutual disturbances

In this paper, a distributed model predictive control scheme is proposed for linear, time-invariant dynamically coupled systems. Uniquely, controllers optimize state and input constraint sets, and exchange information about these—rather than planned state and control trajectories—in order to coordinate actions and reduce the effects of the mutual disturbances induced via dynamic coupling. Mutual disturbance rejection is by means of the tube-based model predictive control approach, with tubes optimized and terminal sets reconfigured on-line in response to the changing disturbance sets. Feasibility and exponential stability are guaranteed under provided sufficient conditions on non-increase of the constraint set parameters

An Excursion-Theoretic Approach to Stability of Discrete-Time Stochastic Hybrid Systems

We address stability of a class of Markovian discrete-time stochastic hybrid systems. This class of systems is characterized by the state-space of the system being partitioned into a safe or target set and its exterior, and the dynamics of the system being different in each domain. We give conditions for $L_1$-boundedness of Lyapunov functions based on certain negative drift conditions outside the target set, together with some more minor assumptions. We then apply our results to a wide class of randomly switched systems (or iterated function systems), for which we give conditions for global asymptotic stability almost surely and in $L_1$. The systems need not be time-homogeneous, and our results apply to certain systems for which functional-analytic or martingale-based estimates are difficult or impossible to get.Comment: Revised. 17 pages. To appear in Applied Mathematics & Optimizatio

Multivariable Feedback Design

xvii, 424 hlm, Ilust : 21 c

Predictive control: A lecture course given in the Aerospace Engineering Faculty TU Delft

These notes were written for a course of 14 two-hour lectures on Model Predictive Control given to students at the Technical University of Delft in November and December 1997.Aerospace Engineerin