MATEC Web Conf.
Volume 210, 201822nd International Conference on Circuits, Systems, Communications and Computers (CSCC 2018)
|Number of page(s)||13|
|Published online||05 October 2018|
Self-Learning Control System Concept for APU Test Cells
COMOTI – Romanian Research & Development Institute for Gas Turbines, Metrology Laboratory 061126 Bucharest, Romania
2 COMOTI – Romanian Research & Development Institute for Gas Turbines, Automation Department 061126 Bucharest, Romania
* Corresponding author: firstname.lastname@example.org
The proposed concept presents an innovative test cell control system, compatible with an existing APU (Auxiliary Power Unit) test cell. The system is essentially a Non-Propulsive Energy (NPE) Power Management Unit that needs to efficiently distribute power among an aircraft’s pneumatic and electrical loads, based on key parameters read from: loads (electrical, pneumatical), a real APU and real-time models of main engines representative to the aircraft. For this, the concept suggests a hardware & software solution, based on the approach of Artificial Neural Network (ANN). The ANN processes all inputs according to a mathematical law trained from existing data sets, such that minimal power loss is considered, given all safety levels are achieved. Development of the neural network is made such that the fastest response time and best performance consist as general goals, and the resulting control system is tested via Hardware-in-the-Loop simulation. Thus, the neural network is also designed to be safe and stable given maximum performance. The hardware solution describes all the equipment included to fulfil the objectives of the concept.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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