Brief paper: Identification of dynamic systems using Piecewise-Affine basis function models

Authors:
Chengtao Wen;Shuning Wang;Xuexiang Jin;Xiaoyan Ma
Affiliations:
Institute of System Engineering, Department of Automation, Tsinghua University, Beijing 100084, PR China;Institute of System Engineering, Department of Automation, Tsinghua University, Beijing 100084, PR China;Institute of System Engineering, Department of Automation, Tsinghua University, Beijing 100084, PR China;LPMC, UMR-CNRS 5617, Montpellier University II, Place E. Bataillon, 34095 Montpellier Cedex 5, France
Venue:
Automatica (Journal of IFAC)
Year:
2007

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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+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.