Nonlinear model predictive controller using neural network

Date

1997-06-12

Author

Karahan, O
Ozgen, C
Halici, U
Leblebicioğlu, Mehmet Kemal

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In this paper, a non-linear Model Predictive Control (MPC) algorithm is proposed which extends the capacities of Linear Model Predictive Controllers to control non-linear systems. A Neural Network (NN) is used to model the deviation of the non-linear system from its linear MPC model. Proposed algorithm is tested in control of an industrial multi-component high purity distillation column by simulation. Results of NN-MPC show high improvement in control of system over linear MPC algorithm.

Subject Keywords

Industrial control, Electrical equipment industry, Testing, Control system synthesis, Prediction algorithms, Predictive control, Nonlinear systems, Nonlinear control systems, Predictive models, Neural networks

URI

https://hdl.handle.net/11511/47163

DOI

https://doi.org/10.1109/icnn.1997.616105

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

O. Karahan, C. Ozgen, U. Halici, and M. K. Leblebicioğlu, “Nonlinear model predictive controller using neural network,” 1997, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47163.