Refined IV-based method for LPV partial differential equation model identification

This paper presents a direct identification method for linear parameter varying models described by partial differential equations in an input-output setting. The continuous space-time model is firstly rewritten as a multiple-input single-output model. The continuous filtering operations are reformulated as a discrete convolution product and a refined instrumental variable technique is developed to efficiently estimate the model parameters. The performance of the proposed method is then illustrated via a representative simulation example.