Adaptive hinging hyperplanes and its applications in dynamic system identification

The model of adaptive hinging hyperplanes (AHH) is proposed in this paper. It is based on multivariate adaptive regression splines (MARS) and generalized hinging hyperplanes (GHH) and shares attractive properties of the two. By making a modification to the basis function of MARS, AHH shows linear property in each subregion. The AHH model is actually a special case of the GHH model, which has a universal representation capability for continuous piecewise linear functions. The approximation ability of the AHH model is proved. The AHH algorithm is developed similar to the MARS algorithm. It is adaptive and can be executed efficiently, hence has power and flexibility to model unknown relationships. The AHH procedure is applied to identifying two dynamic systems and its potential is illustrated.