| 초록 |
As an alternative to "full-fledged" nonlinear model predictive control, we introduced a different model predictive control algorithm that uses LF-LPV prediction models obtained by the LF-LPV subspace identification method. In this way, the problem setup of the standard nonlinear model predictive control approach is avoided and the computational efficiency is significantly improved. When compared with the standard local linearization-based model predictive control which uses linear time-invariant prediction models, subspace-based predictive control using LF-LPV prediction model provides performance closer to that of the nonlinear model predictive control.
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