Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
697634 | Automatica | 2007 | 8 Pages |
Abstract
Piecewise-Affine (PWA) Basis Function AutoRegressive eXogenous (BPWARX) models are proposed in this paper for nonlinear black-box identification. A BPWARX model is a weighted sum of PWA Basis (BPWA) functions, which are the minimum or maximum of n+1n+1 affine functions in n dimensions. Since the BPWA functions have a universal representation capability for continuous PWA functions, the BPWARX models provide better accuracy than the Hinging Hyperplane ARX (HHARX) models with the same number of parameters, and the same order of computational complexity, when using a modified Gauss–Newton algorithm to build the models from input–output data.
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Authors
Chengtao Wen, Shuning Wang, Xuexiang Jin, Xiaoyan Ma,