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Small Body GN&C research report : a robust model predictive control algorithm with guaranteed resolvability

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dc.contributor.author Acikmese, Behcet A.
dc.contributor.author Carson, John M., III
dc.date.accessioned 2008-08-07T22:42:02Z
dc.date.available 2008-08-07T22:42:02Z
dc.date.issued 2005-09-02
dc.identifier.uri http://hdl.handle.net/2014/40902
dc.description.abstract A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2005 en_US
dc.relation.ispartofseries JPL en_US
dc.relation.ispartofseries D-32947 en_US
dc.subject model predictive control algorithm (MPC) en_US
dc.title Small Body GN&C research report : a robust model predictive control algorithm with guaranteed resolvability en_US
dc.type Technical Report en_US


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