Safe Operation of UAVs Using Nonlinear Robust Control and Modular Barrier Functions
The ever-increasing proliferation of smart networks calls for developing robust verification algorithms to ensure the safe behavior of cyber-physical systems. This webinar, presented by Dr. Ghaffari from Wayne State University, aims to facilitate a modular control design to enforce a safety net around unmanned aerial vehicles (UAVs).
System properties and constraints, including underactuated dynamics and actuator saturation, dramatically affect the UAV's maneuverability inside the operational envelope. Moreover, state-of-the-art safety control depends heavily on the specifications of the operational envelope. Thus, Dr. Ghaffari and his team propose a modular technique to transform safety envelopes into position-velocity barriers along each axis of motion. Dr. Ghaffari will show that the proposed modular design guarantees safety and asymptotic stability simultaneously. He will describe how:
- his team derived the closed-form solution for the safety rule as allowable low and high limits of the control command
- their safety design seamlessly integrates with any existing motion control algorithm with minimum modifications
- they handle the nonlinear complexity of the UAV, including system uncertainties and external disturbances and achieve a desirable robust behavior for trajectory and attitude control using the super-twisting control
- carried out the control calibration and tuning on the Autonomous Research Vehicle Studio by Quanser
- conducted extensive experiments to verify the effectiveness of our proposed safety control under realistic operational conditions.
Presenter Bio: Azad Ghaffari received his Ph.D. degree in engineering sciences from the University of California, San Diego, M.S. degree in control engineering, and B.S. degree in electrical engineering from the K. N. Toosi University of Technology, Tehran, Iran. He is currently an assistant professor in the Department of Mechanical Engineering at Wayne State University. His career includes postdoctoral appointments at the University of Michigan, Ann Arbor, and the University of California, San Diego. His work bridges the gap between controls, mechatronics, and energy systems. His research interests include control design for safety-critical cyber-physical systems, distributed supervisory controller design for swapping modularity over smart networks, control of variable sample rate systems, high-precision motion control of servo-systems, aggregate demand response in power systems, extremum seeking and its application to maximum power point tracking in photovoltaic and wind energy conversion systems, sliding mode control, and linear matrix inequalities. He has six years of industrial training on control, automation, and instrumentation of combined cycle power plants, air-cooled condenser systems, biomass reactors, and multi-phase medium-voltage synchronous generators, and switching mode power supplies.
