Failsafe Algorithms for Stabilization and Control of UAS Platforms
Published in University of Nevada, Reno, Computer Science and Engineering, 2014
Rapid increase in the use of Unmanned Autonomous Systems (UAS) has caused the safety of these platforms to become a high priority. One main safety issue with UAS platforms is motor failure. In order to increase the safety of these platforms in the event of such a failure, a failsafe mechanism can be used to stabilize and control the UAS platform.
Without a failsafe mechanism, the loss of a motor will cause the platform to fall out of the sky. This can cause serious injury to the people and property in the vicinity of the UAS. Using a failsafe mechanism would prevent these types of falls from occurring thereby increasing the safety of UAS during flight and minimizing damage to the surroundings.
With the loss of a motor, the dynamics of a UAS platform will change. By taking advantage of these new dynamics, a failsafe algorithm can use the reduced attitude to return partial control to the platform. This partial control can be used to stabilize the platform and maneuver it a short distance in order to bring it safely to the ground. We have developed failsafe algorithms to deal with motor failure on two different types of UAS: asymmetrical quadrocopters and hexacopters. The algorithm for a quadrocopter is adapted from a feedback linearization approach. One of the hexacopter algorithms is also adapted from this approach. The other hexacopter algorithm is adapted from a redistributed pseudo inverse method. The quadrocopter algorithm maintains control for a long enough period of time that a safe landing is possible. The first hexacopter algorithm maintains control by shutting off the opposing motor, thus allowing the platform to fly as a quadrocopter and land safely. The second hexacopter algorithm maintains control with five motors, but it’s much less stable than the feedback linearization based algorithm.
Role: Lead undergraduate researcher.
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