Study of Advanced Control Based on the RBF Neural Network Theory in Diesel Engine Speed Control

Based on radial basis function (RBF) neural network (NN) theory, RBF-Proportional Integral Derivative (PID) diesel engine speed control is proposed. The algorithm has strong self-learning ability and strong adaptive ability, and is able to optimize the control parameters of the speed loop controller...

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Bibliographic Details
Published inSAE International journal of engines Vol. 13; no. 1; pp. 63 - 76
Main Authors Zhao, Guo-Feng, Long, Yun, Ding, Shun-Liang, Yang, Li-Ping, Song, En-Zhe, Ma, Xiu-Zhen
Format Journal Article
LanguageEnglish
Published Warrendale SAE International 01.01.2020
SAE International, a Pennsylvania Not-for Profit
Subjects
Adaptive control
Algorithms
Analysis
Computer simulation
Control algorithms
Control theory
Controllers
Diesel engine
Diesel engines
Diesel motor
Internal combustion engine industry
Machine learning
Neural networks
Proportional integral derivative
Radial basis function
RBF Neural Network
Recovery time
Simulation
Speed control
Stability
China
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Summary:Based on radial basis function (RBF) neural network (NN) theory, RBF-Proportional Integral Derivative (PID) diesel engine speed control is proposed. The algorithm has strong self-learning ability and strong adaptive ability, and is able to optimize the control parameters of the speed loop controller in real time. A series of simulations are carried out with different initial weights. Simulation results reveal that initial weights have little effect on RBF-PID control performance. A STM32 MCU-based controller is developed according to the calculation requirement. Experiments are carried out on a D6114 diesel engine generator to verify the proposed speed control algorithm. The simulation results are in agreement with the experimental results. The results show that the influence of initial weights on RBF-PID control algorithm is smaller than that on BP-PID control algorithm. When RBF-PID control algorithm is adopted, the steady speed fluctuation rate is 0.4%. When sudden load is carried out, the speed recovery time is 2.1 s and the instantaneous adjustment rate is 4.93%. When sudden unload simulation is carried out, the speed recovery time is 2.2 s and the instantaneous adjustment rate is 5.27%. Speed control performance of diesel engine has been greatly improved.
ISSN:1946-3936
1946-3944
1946-3944
DOI:10.4271/03-13-01-0005