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Article: Recent studies by V. Hagganozaki and co-authors add new data to control systems findings.
- Article from:
- Robotics & Machine Learning
- Article date:
- February 9, 2009
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"Radial basis function autoregressive with exogenous inputs (RBF-ARX) models have been shown to be useful in modeling the nonlinear behavior of a variety of complex systems. In particular, Peng et al. have shown how the RBF-ARX model may be used to model the selective catalytic reduction (SCR) process for real data from a thermal power plant, and have simulated control of the plant using the generalized predictive control (GPC) method of Clarke et al. very effectively," scientists in Tokyo, Japan report.
"However, the GPC approach requires constrained nonlinear optimization at each control step, which is time-consuming and computationally very expensive. Here, in ...