This paper describes a real-time control method for non-linear systems based on model predictive control. The model used for the prediction is a neural network because of its ability to represent non-linear systems, its ability to be differentiated, and its simplicity of use. The feasibility and the performance of the method, based on on-line linearization, are demonstrated on a turbocharged spark-ignited engine application, where the simulation models used are very accurate and complex. The results, first in simulation and then on a test bench, show the implementation of the proposed control scheme in real time.
Exact and Linearized Neural Predictive Control: A Turbocharged SI Engine Example
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Colin, G., Chamaillard, Y., Bloch, G., and Charlet, A. (February 12, 2007). "Exact and Linearized Neural Predictive Control: A Turbocharged SI Engine Example." ASME. J. Dyn. Sys., Meas., Control. July 2007; 129(4): 527–533. https://doi.org/10.1115/1.2745881
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