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Intelligent Robust Controller for Hybrid Electric UAVs


OBJECTIVE: Develop and demonstrate an intelligent robust controller that can be applied to control and optimize the energy and propulsion of small hybrid electric unmanned aerial vehicles (UAVs). 

DESCRIPTION: The demand of UAVs for military and civil missions has greatly increased in the last two decades because of their performance in battle fields and rescue operations. The use of UAVs, especially UAVs in the range of 10 - 100 lbs., is escalating, predominately due to cost savings over manned systems. In his recent “Report on Technological Horizons: A Vision for Air Force Science and Technology During 2010-2030”, the Chief Scientist of the Air Force makes UAV autonomy the number one research and development priority. The development of energy-efficient and low-cost propulsion systems for UAVs by implementing hybrid electric concepts is critical both for sustainable energy as well as mission performance. To meet the needs of United States Air Force and commercial aviation, actions to increase energy efficiency are essential. The benefit of hybrid electric propulsion systems is that they provide an enormous advantage over conventional petrol powered vehicles in terms of energy efficiency, flight duration, and noise signature. A hybrid propulsion system can be an integration of two or more power units such as IC engine, motor-generator/battery, fuel cell, jet engine or solar cell. To effectively control and minimize the energy flow of the hybrid electric propulsion system, an intelligent robust controller is sought. It is intended to minimize the weight and optimize the energy efficiency of the hybrid systems for all operation conditions. The objective of the intelligent control system is to optimize the energy consumption and regeneration between the power units such that the hybrid system can operate in the highest efficient condition. The control system will be provided with automatic and manual modes. The default mode is automatic; the manual mode is operated by the pilot of UAV and may be switched to different modes including silent mode if the mission is required. In Phase II, use modern sensor and actuator technology to monitor and control the energy flow and regeneration; and to manage the operation of engine and motor/generator such that the system can effectively switch among individual (engine or motor) mode, dual mode, automatic mode, manual mode, battery charging, etc. 

PHASE I: Develop an intelligent robust controller that can be used to control the hybrid electric propulsion system for UAVs. The configuration of the powertrain architecture consists of an automatic gearbox, an electric motor, power electronics, a battery, a clutch and a turbocharged spark-ignited internal combustion engine, etc. The hybrid test models could also consist of inline and planetary gear configurations to be designed and integrated with the controller. Preliminary tests of these hybrid systems will be conducted. 

PHASE II: Fully develop the prototypes for above hybrid configurations that are implemented with the intelligent controller and demonstrate the capability of the hybrid UAVs by conducting field tests with various flight patterns and payloads in order to evaluate and improve the performance of the system. 

PHASE III: Military applications of this effort may include C-ISR and C-AIED missions. Commercial applications of this technology that address possible counter-terrorist threat activities in the civilian sector. 


1: Tobias Nuesch *, Philipp Elbert, Michael Flankl, Christopher Onder and Lino Guzzella, "Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs.", Energies 2014, 7, 834-856

2:  doi:10.3390/en

3:  L. Doitsidis, K. P. Valavanis, N. C. Tsourveloudis and M. Kontitsis, "A Framework for Fuzzy Logic Based UAV Navigation and Control," Proceedings of the 2004 IEEE International Conference on Robotics & Automation New Orleans, LA, 2004.

4:  Liwei Qiu, Guoliang Fan, Jianqiang Yi and Wensheng Yu, "Robust Hybrid Controller Design Based on Feedback Linearization and µ Synthesis for UAV," Proceedings of the 2009 Second International Conference on Intelligent Computation Technology and Automat

KEYWORDS: UAV, Controllers, Propulsion Systems, *electric Power, *hybrid Systems, Velocity, Computer Programs, Optimization, Intelligence, Disasters, Monitoring, Networks, Unmanned, Electricity, Lithium Batteries, Surveillance, Reconnaissance, Aspect Ratio, Electri 


Dr. Alireza Behbahani (AFRL/RQTE) 

(937) 255-5637 

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