Editorial
Speed Control of Marine Diesel Engine Based on Lyapunov Neural Network Combined with Adaptive Backpropagation Algorithm
@ARTICLE{10.4108/tsoe.11168, author={Diem Nguyen and Thanh-Duy Nguyen and Thanh-Trung Pham and Van-Minh Nguyen}, title={Speed Control of Marine Diesel Engine Based on Lyapunov Neural Network Combined with Adaptive Backpropagation Algorithm}, journal={EAI Endorsed Transactions on Transportation Systems and Ocean Engineering}, volume={1}, number={1}, publisher={EAI}, journal_a={TSOE}, year={2025}, month={12}, keywords={marine diesel engine, speed control system, neural network, backpropagation, lyapunov stability}, doi={10.4108/tsoe.11168} }- Diem Nguyen
Thanh-Duy Nguyen
Thanh-Trung Pham
Van-Minh Nguyen
Year: 2025
Speed Control of Marine Diesel Engine Based on Lyapunov Neural Network Combined with Adaptive Backpropagation Algorithm
TSOE
EAI
DOI: 10.4108/tsoe.11168
Abstract
The speed control system of vessel diesel engine plays a crucial role in the operation and utilization of the machinery, directly impacting maritime economic efficiency. All types of vessels operating at sea require a system to control and monitor the speed of diesel engines, ensuring that the rotation speed of the engines remains stable in the face of changes in load and the impact of the marine environment. This study proposes a marine diesel engine speed control system based on a Lyapunov-Stabilized Neural Network (LSNN) with a novel adaptive backpropagation algorithm. Accordingly, unlike the traditional gradient-based backpropagation algorithm, the weights of the Neural Network (NN) are adjusted according to an adaptive law. In addition, the evaluation of the stability of the NNs using Lyapunov theory is also discussed. The stability of the speed system with the proposed controller is evaluated by the Bode stability criterion. Simulating and comparing the proposed solution with the traditional weight update the NN in various scenarios to demonstrate its effectiveness.
