Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
697528 | Automatica | 2009 | 5 Pages |
Abstract
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 insight into the reasons underlying the high computational complexity of several recently proposed algorithms and point out the need for developing computationally tractable relaxations.
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Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Mario Sznaier,