Cyber-physical optimization of small unmanned aircraft systems with thermal consideration

Coloe, Brandon; Atkins, Ella M.

doi:10.1109/acc.2016.7525109

Cited by 2 publications

(3 citation statements)

References 27 publications

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“…In our previous work [ 35 ], we optimized a UAS inspection mission over an integrated CPS cost function, including mission time, physical actuator and computing system energy consumption, payload information (gaps) and processor utilization. More recently, we added physical (battery, motor) and computing system thermal costs and constraints [ 172 ].…”

Section: Trajectory and Task Optimization And Planning For Cyber-pmentioning

confidence: 99%

“…For example, processor power and thermal regulation [ 164 ] consider physical environment impact on cores, but do not optimize physical mobility/actuation (e.g., by demanding less torque, thereby lowering heat production in the (self-driving) car’s engine compartment). Similarly, in our own work [ 35 , 172 ], a UAS trajectory is itself optimized over cyber-physical terms, including the energy used and heat generated by propulsion and computing systems as a function of physical state and processor utilization trajectories. To offer the benefits of dynamic sampling alongside the critical guarantees of time-triggered sampling, very recently, optimal sampling and control techniques have arisen.…”

Section: Trajectory and Task Optimization And Planning For Cyber-pmentioning

confidence: 99%

“…Mobile systems, such as UAS, carry limited energy resources, resulting in hard energy constraints, while vehicle stability, environmental hazards, etc ., impose real-time transit and computing constraints. In our previous work [ 35 , 172 ], we developed a suite of physical, cyber and combined cost function to optimize UAS pipeline inspection. A gimbal-mounted camera onboard a UAS provided imagery, which was processed by a real-time task.…”

Section: Trajectory and Task Optimization And Planning For Cyber-pmentioning

confidence: 99%

See 2 more Smart Citations

Optimization and Control of Cyber-Physical Vehicle Systems

Bradley

Atkins

2015

Sensors

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A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

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Section: Trajectory and Task Optimization And Planning For Cyber-pmentioning

confidence: 99%