- Title
- Adaptive-pole selection in the Laguerre parametrisation of model predictive control to achieve high performance
- Creator
- Hemmasian Ettefagh, Massoud; De Dona, Jose; Towhidkhah, Farzad; Naraghi, Mahyar
- Relation
- International Journal of Systems Science Vol. 52, Issue 16, p. 3539-3555
- Publisher Link
- http://dx.doi.org/10.1080/00207721.2021.1933252
- Publisher
- Taylor & Francis
- Resource Type
- journal article
- Date
- 2021
- Description
- In this paper, we study an adaptive method to select online the pole value for a Laguerre scheme in Model Predictive Control (MPC) that yields high performance. It has been observed that, while still using a small numbers of decision variables, the location of the pole affects the closed-loop behaviour significantly. In the present paper, an adaptive algorithm is developed to systematically improve the closed-loop performance of the system as well as the volume of the feasible region and robust feasible region in the case of using a small numbers of decision variables. In order to do this, a method to select a pole value that yields high performance for the initial condition of the system is proposed. The method generates a lookup table of the high-performance pole value obtained through off-line computations. Then, the table is used to assign the pole in the online process. Closed-loop stability for the scheme is established using sub-optimality arguments. Simulations illustrate the suggested method's effectiveness to achieve a balance between performance, optimality, and computational load.
- Subject
- model predictive control; Laguerre; adaptive-pole tuning; suboptimal; computation time
- Identifier
- http://hdl.handle.net/1959.13/1472581
- Identifier
- uon:48882
- Identifier
- ISSN:0020-7721
- Language
- eng
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