A General Control Horizon Extension Method for Nonlinear Model Predictive Control
Zhang H.T. and Li H.X.
Industrial & Engineering Chemistry Research, Volume 46, Number 26, Pages 9179-9189, 2007Abstract
In the nonlinear model predictive control (NMPC) field, it is well-known that the multi-step control approach is superior to the single-step one when dealing with high-order nonlinear systems. In the multi-step control approach, however, the online minimization of a 2-norm square objective function over a control horizon of length M always requires solving a set of complex polynomial equations, for which no definite solution exists so far. Besides, the complex nature of the receding horizon optimization also causes additional problems to its closed-loop stability analysis. With these two serious challenges in mind, taking a Volterra-Laguerre model-based NMPC for discussion, we propose a general technique to extend the control horizon with the assistance of Groebner basis, which transforms the set of complex polynomial equations into a much simpler form. We prove the closed-loop stability of the algorithm in the sense that the input and output series are both mean-square bounded. Finally, the efficiency of this improved algorithm is examined on an industrial constant pressure water supply system. Compared with the conventional NMPC schemes, the proposed method with the control horizon extension has shown a great potential to control a wide range of nonlinear dynamic systems.
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BibTex Entry
- @Article{,
- author = {Zhang H.T. and Li H.X.},
- journal = {Industrial & Engineering Chemistry Research},
- title = {A General Control Horizon Extension Method for Nonlinear Model Predictive Control},
- year = {2007},
- number = {26},
- pages = {9179-9189},
- volume = {46}
- }
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