On the Design of Regularized Explicit Predictive Controllers From Input–Output Data

On the wave of recent advances in data-driven predictive control, we present an explicit controller that can be constructed from a batch of input/output data only. The proposed explicit law is built upon a regularized data-driven control problem, so as to guarantee the uniqueness of the explicit predictive controller and to endow it with noise handling capabilities. The effectiveness of the retrieved explicit law and the repercussions of regularization on noise handling is analyzed on a benchmark simulation example.