| Citation: | SHAN Ruibin, LI Qiuhong, HE Fenglin, et al. Model predictive control based on ADMM for aero-engine[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(6): 1240-1247. doi: 10.13700/j.bh.1001-5965.2018.0599(in Chinese)
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In order to improve the real time performance of the nonlinear model predictive control (MPC) for aero-engine, an alternating direction method of multipliers (ADMM) was applied to the receding horizon optimization of MPC. The predictive equation was constructed based on the state space model. The auxiliary variables and dual variables were introduced to rewrite the quadratic control performance index and engine constraints into a new form which could be solved by ADMM. Simulations on a component level model show that the single input variable model predictive control based on ADMM achieves both high-quality reference tracking performance and efficient limit management of aero-engine. Compared with interior point method (IPM), the real time performance of ADMM is much better than that of IPM at different magnitude control commands, and the increment of time consumption is much less than that of IPM with the increase of the predictive horizon. The effectiveness of the ADMM in MPC is valid.
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