Difference between revisions of "Robust Model Predictive Control with a Safety Mode: Applied to Small-Body Proximity Operations"

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|Authors=John Carson, Behcet Acikmese, Richard Murray, and Douglas MacMynowski
|Authors=John Carson, Behcet Acikmese, Richard Murray, and Douglas MacMynowski
|Source=AIAA Guidance, Navigation and Control Conference and Exhibit, Guidance, Navigation, and Control and Co-located Conferences, 2008
|Source=AIAA Guidance, Navigation and Control Conference and Exhibit, Guidance, Navigation, and Control and Co-located Conferences, 2008
|Abstract=See all ›
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Robust Model Predictive Control with a Safety Mode: Applied to Small-Body Proximity Operations
 
Conference Paper · August 2008 with 5 Reads
DOI: 10.2514/6.2008-7243
Conference: AIAA Guidance, Navigation and Control Conference and Exhibit
 
1st John M Carson
14.22 · NASA
 
2nd Behçet Açıkmeşe
26.27 · University of Washington Seattle
 
3rd Richard M. Murray
40.05 · California Institute of Technology
 
4th Douglas Macmartin
32.87 · California Institute of Technology
Abstract
Safe and robust G&C (Guidance and Control) algorithms for onboard implementation are developed by augmenting a model predictive control technique with a safety mode. The application example herein is spacecraft small-body proximity operations where model and constraint uncertainty warrant G&C algorithms with a degree of autonomous, onboard decision capability. The algorithm enforces state and control constraints and merges two operational modes: (I) standard mode guides the spacecraft to the proximity of a target state in a robust and resolvable model-predictive manner; (II) safety mode, if activated, maintains the spacecraft near a safety reference for all time. The algorithm utilizes separate feedforward and feedback components. In standard mode, the feedforward guidance solutions come from a way-point generation algorithm that uses a discrete linear-time-varying dynamics model. This approach provides a convex formulation of the problem (solvable onboard as a second-order cone program) that includes control and state constraints; the safety-mode availability adds a constraint in this standard-mode formulation as well. The feedback guarantees standard-mode resolvability to update the guidance profile in a robust, model-predictive manner. In safety mode, an offline-designed feedforward policy with the added feedback maintains the spacecraft in a hovering state in the proximity of its position at safety-mode activation time; this provides robustness to unexpected state-constraint changes such as unexpected ground proximity during landing operations. A simulation demonstrating both the standard and safety modes is provided for a spacecraft autonomous-descent scenario toward a small asteroid with an uncertain gravity model and errors in the surface altitude constraint.
Safe and robust G&C (Guidance and Control) algorithms for onboard implementation are developed by augmenting a model predictive control technique with a safety mode. The application example herein is spacecraft small-body proximity operations where model and constraint uncertainty warrant G&C algorithms with a degree of autonomous, onboard decision capability. The algorithm enforces state and control constraints and merges two operational modes: (I) standard mode guides the spacecraft to the proximity of a target state in a robust and resolvable model-predictive manner; (II) safety mode, if activated, maintains the spacecraft near a safety reference for all time. The algorithm utilizes separate feedforward and feedback components. In standard mode, the feedforward guidance solutions come from a way-point generation algorithm that uses a discrete linear-time-varying dynamics model. This approach provides a convex formulation of the problem (solvable onboard as a second-order cone program) that includes control and state constraints; the safety-mode availability adds a constraint in this standard-mode formulation as well. The feedback guarantees standard-mode resolvability to update the guidance profile in a robust, model-predictive manner. In safety mode, an offline-designed feedforward policy with the added feedback maintains the spacecraft in a hovering state in the proximity of its position at safety-mode activation time; this provides robustness to unexpected state-constraint changes such as unexpected ground proximity during landing operations. A simulation demonstrating both the standard and safety modes is provided for a spacecraft autonomous-descent scenario toward a small asteroid with an uncertain gravity model and errors in the surface altitude constraint.
|URL=http://arc.aiaa.org/doi/abs/10.2514/6.2008-7243
|URL=http://arc.aiaa.org/doi/abs/10.2514/6.2008-7243

Latest revision as of 13:33, 17 May 2016

Title Robust Model Predictive Control with a Safety Mode: Applied to Small-Body Proximity Operations
Authors John Carson, Behcet Acikmese, Richard Murray, and Douglas MacMynowski
Source AIAA Guidance, Navigation and Control Conference and Exhibit, Guidance, Navigation, and Control and Co-located Conferences, 2008
Abstract Safe and robust G&C (Guidance and Control) algorithms for onboard implementation are developed by augmenting a model predictive control technique with a safety mode. The application example herein is spacecraft small-body proximity operations where model and constraint uncertainty warrant G&C algorithms with a degree of autonomous, onboard decision capability. The algorithm enforces state and control constraints and merges two operational modes: (I) standard mode guides the spacecraft to the proximity of a target state in a robust and resolvable model-predictive manner; (II) safety mode, if activated, maintains the spacecraft near a safety reference for all time. The algorithm utilizes separate feedforward and feedback components. In standard mode, the feedforward guidance solutions come from a way-point generation algorithm that uses a discrete linear-time-varying dynamics model. This approach provides a convex formulation of the problem (solvable onboard as a second-order cone program) that includes control and state constraints; the safety-mode availability adds a constraint in this standard-mode formulation as well. The feedback guarantees standard-mode resolvability to update the guidance profile in a robust, model-predictive manner. In safety mode, an offline-designed feedforward policy with the added feedback maintains the spacecraft in a hovering state in the proximity of its position at safety-mode activation time; this provides robustness to unexpected state-constraint changes such as unexpected ground proximity during landing operations. A simulation demonstrating both the standard and safety modes is provided for a spacecraft autonomous-descent scenario toward a small asteroid with an uncertain gravity model and errors in the surface altitude constraint.
Type Conference paper
URL http://arc.aiaa.org/doi/abs/10.2514/6.2008-7243
Tag camm08-aiaa
ID 2008
Funding
Flags