Adaptive neural tracking control for automotive engine idle speed regulation using extreme learning machine
Author:
Funder
University of Macau
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-019-04482-5.pdf
Reference20 articles.
1. Balluchi A, Zoncu M (2004) A nonlinear hybrid model of a 4-cylinder engine for idle speed control. In: Test case for the computation and control European project
2. Howell MN, Best MC (2000) On-line PID tuning for engine idle-speed control using continuous action reinforcement learning automata. Control Eng Pract 8(2):147–154. https://doi.org/10.1016/S0967-0661(99)00141-0
3. Zhang J, Gao J, Shen T (2016) Adaptive idling control scheme and its experimental validation for gasoline engines. Sci China Inf Sci 60(2):022203. https://doi.org/10.1007/s11432-016-0296-3
4. Banarezaei S, Shalchian M (2018) Design of a model-based fuzzy-PID controller with self-tuning scaling factor for idle speed control of automotive engine. Iran J Sci Technol Trans Electr Eng. https://doi.org/10.1007/s40998-018-0095-z
5. Mu H, Li X, Tang J (2017) Study with fuzzy self-turning PID controller on idle speed controlling of automobile. Paper presented at the 2017 Chinese Automation Congress (CAC), 20–22 Oct 2017
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