Modeling and Control of Dual-Motored Tail-Sitting Flying Wing Using a Fuzzy Logic Pid Controller
| dc.contributor.author | Sebolt, Avery Jackson | en |
| dc.contributor.committeechair | Kochersberger, Kevin Bruce | en |
| dc.contributor.committeemember | Cohen, Kelly | en |
| dc.contributor.committeemember | Woolsey, Craig A. | en |
| dc.contributor.department | Aerospace and Ocean Engineering | en |
| dc.date.accessioned | 2022-11-09T09:00:16Z | en |
| dc.date.available | 2022-11-09T09:00:16Z | en |
| dc.date.issued | 2022-11-08 | en |
| dc.description.abstract | With large-scale implementation of drones having begun and numerous companies competing to be among the original players in the market, there lies a large potential for novel drone designs to be created and flown. These novel designs are the ones that were largely ignored in the previous century due to the physical constraints of having a crewed cockpit, but uncrewed aerial vehicles, or UAVs, have opened a floodgate of potential design spaces that may be explored which were previously impossible. The hybrid vertical take-off and landing, VTOL, UAV is one aircraft that presents a potential solution to the classic trade-off of the traditional VTOL's range and endurance limitations versus the fixed wing's required infrastructure. An aircraft known as the Flite Test Spear is used to examine fuzzy logic control and is one such hybrid VTOL that uses large control surfaces and throttle control to maneuver itself for take-offs and landings in a tail-sitting orientation before transitioning to forward, fixed-wing flight. Current flight controllers used in operation on hybrid VTOL aircraft rely on a control law state machine where given a pre-identified aircraft state, the controller enters a transitioning maneuver that takes the aircraft from a VTOL to fixed wing flight regime, or vice versa. Each flight regime is operated by a PID controller with different gains and control input realizations. A modification to this principle is first examined by using fuzzy logic PID gain modification for increased response time and reduced overshoot. Reducing overshoot is of particular interest in this case as, on an aircraft such as this, it has the potential for entering undesirable and unrecoverable states, especially during its transition. Secondly, a mixing of the two flight controllers using a fuzzy logic system was implemented to combine the two controllers' outputs and potentially smooth this transition for safer, more efficient flight. The fuzzy logic controlled mixing of the two VTOL and fixed wing controllers was not proven to provide a more desirable response within the scope of the simulation, however, performed equally as well to that of the current state machine response. The gain scheduling fuzzy systems implemented in the controller have shown to decrease overshoot of the aircraft when given commands to different states, but respond slower than their conventional counterparts. Promise in the reduction of the overshoot error and their lightweight construction leads to the conclusion that implementation on a prototype aircraft would be worthwhile for further testing. | en |
| dc.description.abstractgeneral | Drones play a larger role in our daily lives than they ever have before. With the work being performed by Google Wing to begin last-mile delivery of household consumer goods to the success of companies like Zipline and Swoop Aero in delivering emergency medical supplies to remote locations in low-resource areas, drones are being increasingly deployed, and their use will continue to grow if current trends continue. Like all burgeoning markets, competition is driving innovation to seek new market sectors and pushing the stagnant players out. In order to distinguish themselves, many companies have been creating their own drones for whichever sector of the drone market they wish to compete in. Whether that be consumer good delivery or aerial imagery, these challenges create numerous problems that some drones handle better than others. This has led to a large investment into the research and development of drones that best suit the needs of whatever mission has to be performed. Drones that act similarly to conventional aircraft such as planes or helicopters may serve as the best solution for a variety of problem statements, but because the need for a pilot in the cockpit is no longer necessary, solutions that were previously impossible to implement due to human factors can now be explored fully. With such an explosion in the design space of drones, the control algorithms needed to operate them must follow suit. This paper attempts to explain an alternative to one of the most common controllers in use today known as the PID. A modification to this controller using a technique known as fuzzy logic is made to increase the performance of experimental drone types without the need of an extensive, costly research and development phase that is necessary for crewed aircraft. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:35428 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/112544 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Drone | en |
| dc.subject | Control | en |
| dc.subject | Fuzzy Logic | en |
| dc.title | Modeling and Control of Dual-Motored Tail-Sitting Flying Wing Using a Fuzzy Logic Pid Controller | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Aerospace Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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