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System Identification and Controller Implementation of a Centrifugal Compressor for Circulation Control Applications

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Abstract

This paper describes a comprehensive methodology to reduce the power penalties of an Air Supply Unit (ASU) used in Circulation Control Unmanned Aerial Vehicles (UC2AVs). Circulation Control (CC), which is an active flow control technique that can be used on fixed-wing aircraft to achieve lift augmentation, requires the use of an efficient CC system on-board. The experimental testbed for a CC system and the development and integration of both a PID and Fuzzy Logic (FL) control scheme are presented in this paper. Ground test experimental results indicate that power penalties can be minimized throughout the flight envelope. The results indicate that the behavior of both controllers exhibits a correlation to the simulation data above 67%. Additionally, both controllers present similar energy usage characteristics, when applied throughout a simulated flight envelope. Results also show that PI control displays a faster rise time and less overshoot than FL control in most cases, but also a longer settling time. Overall the PI controller displays better regulation of the dynamics of the CC system’s behavior. The use of the active CC regulation systems described in this study provides opportunities for application to commercial UAV technology, providing important advances in this rapidly growing field.

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Authors and Affiliations

  1. Department of Electrical, Computer Engineering, Daniel Felix Ritchie School of Engineering, Computer Science, University of Denver, Denver, CO, USA

    Cameron Rosén, Konstantinos Kanistras, Pranith Chander Saka, Kimon P. Valavanis & Matthew J. Rutherford

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  1. Cameron Rosén
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  2. Konstantinos Kanistras
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  3. Pranith Chander Saka
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  4. Kimon P. Valavanis
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  5. Matthew J. Rutherford
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Correspondence to Cameron Rosén.

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Rosén, C., Kanistras, K., Saka, P.C. et al. System Identification and Controller Implementation of a Centrifugal Compressor for Circulation Control Applications. J Intell Robot Syst 91, 629–650 (2018). https://doi.org/10.1007/s10846-017-0756-6

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  • DOI: https://doi.org/10.1007/s10846-017-0756-6

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