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A set-theoretic Failure Model and Effect Management (FMEM) strategy for stuck/jammed actuators in systems with redundant actuators is considered. This strategy uses a reference governor for command tracking while satisfying state and control constraints and, once the failure mode is known, generates a recovery command sequence during mode transitions triggered by actuator failures. In the paper, this FMEM strategy is enhanced with a scheme to detect and isolate failures within a finite time, and to handle unmeasured set-bounded disturbance inputs. A numerical example is reported to illustrate the offline design process and the online operation with the proposed approach. 

This paper illustrates an approach to integrate learning into spacecraft automated rendezvous, proximity maneuvering, and docking (ARPOD) operations. Spacecraft rendezvous plays a significant role in many spacecraft missions including orbital transfers, ISS re-supply, on-orbit refueling and servicing, and debris removal. On one hand, precise modeling and prediction of spacecraft dynamics can be challenging due to the uncertainties and perturbation forces in the spacecraft operating environment and due to multi-layered structure of its nominal control system. On the other hand, spacecraft maneuvers need to satisfy required constraints (thrust limits, line of sight cone constraints, relative velocity of approach, etc.) to ensure safety and achieve ARPOD objectives. This paper considers an application of a learning-based reference governor (LRG) to enforce constraints without relying on a dynamic model of the spacecraft during the mission. Similar to the conventional Reference Governor (RG), the LRG is an add-on supervisor to a closed-loop control system, serving as a pre-filter on the command generated by the ARPOD planner. As the RG, LRG modifies, if it becomes necessary, the command to a constraint-admissible reference to enforce specified constraints. The LRG is distinguished, however, by the ability to rely on learning instead of an explicit model of the system, and guarantees constraints satisfaction during and after the learning. Simulations of spacecraft constrained relative motion maneuvers on a low Earth orbit are reported that demonstrate the effectiveness of the proposed approach. 

This paper proposes a Failure Mode and Effect Management (FMEM) strategy for constrained systems with redundant actuators based on the combined use of constraint admissible and recoverable sets. Several approaches to ensure reconfiguration of the system without constraint violation in the event of actuator failures are presented. Numerical simulation results are reported.