Computational burden reduction in Set-membership Hammerstein system identification
نویسندگان
چکیده
منابع مشابه
Computational burden reduction in Set-membership Hammerstein system identification
Hammerstein system identification from measurements affected by bounded noise is considered in the paper. First, we show that the computation of tight parameter bounds requires the solution to nonconvex optimization problems where the number of decision variables increases with the length of the experimental data sequence. Then, in order to reduce the computational burden of the identification ...
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This paper analyzes the computational complexity of set membership identification of Hammerstein and Wiener systems. Its main results show that, even in cases where a portion of the plant is known, the problems are generically NP-hard both in the number of experimental data points and in the number of inputs (Wiener) or outputs (Hammerstein) of the nonlinearity. These results provide new insigh...
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This work is concerned with identification of Hammerstein systems whose outputs are measured by set-valued sensors. The system consists of a memoryless nonlinearity which is polynomial and possibly non-invertible, followed by a linear subsystem. The parameters of linear and nonlinear parts are unknown but have known orders. Input design, identification algorithms, and their essential properties...
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ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 2011
ISSN: 1474-6670
DOI: 10.3182/20110828-6-it-1002.02090