Computationally Efficient Set-based Predictive Control for Grid-tied Inverters
| Autor: | Sandor Iles, Jadranko Matuško, Viktor Sunde, Renato Babojelic |
|---|---|
| Přispěvatelé: | Ramón Blasco-Gimenez, Spain |
| Rok vydání: | 2021 |
| Předmět: |
Sequence
Mathematical optimization Computer science power converters model predictive control finite control set robust control fast gradient projection method 020206 networking & telecommunications 02 engineering and technology Function (mathematics) Optimal control Constraint (information theory) Set (abstract data type) Model predictive control Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Set theory |
| Zdroj: | ICIT |
| DOI: | 10.1109/icit46573.2021.9453631 |
| Popis: | This paper presents a fast gradient projection model predictive control algorithm based on a sequence of 1-step controllable sets for controlling a grid-tied converter with an LCL filter. The proposed method uses a set membership constraint on the first state, which ensures finite time convergence to the terminal set. To use the fast gradient projection method to solve the finite-time optimal control problem with state constraints, we adopted an approach where the set membership constraint is transformed into the corresponding input constraint as a function of the current state. In this way, no significant additional computational load was introduced, allowing the MPC algorithm to be solved efficiently. |
| Databáze: | OpenAIRE |
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