A computationally efficient model predictive control strategy for linear systems with integer inputs
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||9|
|Journal||IEEE Transactions on Control Systems Technology|
|Publication status||Published - Jul 2016|
|Publication type||A1 Journal article-refereed|
For linear systems with integer inputs, the model predictive control problem with output reference tracking is formulated as an integer least-squares (ILS) problem. The ILS problem is solved using a modified sphere decoding algorithm, which is a particular branch-and-bound method. To reduce the computational complexity of the sphere decoder, a reduction algorithm is added as a preprocessing stage to reshape the search space in which the integer solution lies. The computational complexity of the proposed algorithm is modest, enabling its implementation in a real-time system even when considering long prediction horizons. A variable-speed drive system with a three-level voltage source inverter serves as an illustrative example to demonstrate the effectiveness of the proposed algorithm.