This paper describes an efficient method for scheduling an energy-consuming sensor sparingly in combination with an on-off controller, specifically for a finite horizon control problem in which only end states are critical. In certain low-power applications, such as autonomous micro-robotics, on-off controllers can be very efficient in operating piezoelectric actuators (and other capacitive actuation schemes) compared to traditional analog and PWM controllers. However, with existing sensing circuitry, sensing at the same frequency as control can be prohibitively expensive. Instead, a method is presented for best scheduling a limited number of sensor measurements and updates to control inputs during a finite horizon on-off control problem, in response to Gaussian disturbances and measurement noise. To simplify the problem, a lower bound for the expected value of a quadratic error function of the end states is found, which permits rapid evaluation of candidate sensor times.
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ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
October 17–19, 2012
Fort Lauderdale, Florida, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4531-8
PROCEEDINGS PAPER
A Near-Optimal Sensor Scheduling Strategy for an On-Off Controller With an Expensive Sensor
Biju Edamana,
Biju Edamana
University of Michigan, Ann Arbor, MI
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Kenn Oldham
Kenn Oldham
University of Michigan, Ann Arbor, MI
Search for other works by this author on:
Biju Edamana
University of Michigan, Ann Arbor, MI
Kenn Oldham
University of Michigan, Ann Arbor, MI
Paper No:
DSCC2012-MOVIC2012-8696, pp. 281-290; 10 pages
Published Online:
September 17, 2013
Citation
Edamana, B, & Oldham, K. "A Near-Optimal Sensor Scheduling Strategy for an On-Off Controller With an Expensive Sensor." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 3: Renewable Energy Systems; Robotics; Robust Control; Single Track Vehicle Dynamics and Control; Stochastic Models, Control and Algorithms in Robotics; Structure Dynamics and Smart Structures; Surgical Robotics; Tire and Suspension Systems Modeling; Vehicle Dynamics and Control; Vibration and Energy; Vibration Control. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 281-290. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8696
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