A novel approach to adaptive direct neurocontrol is discussed in this paper. The objective is to construct an adaptive control scheme for unknown time-dependent nonlinear plants without using a model of the plant. The proposed approach is neural-network based and combines the self-tuning...

Empirical modeling of the industrial antibiotic fed-batch fermentation process is discussed in this paper. Several methods including neural networks, genetic algorithms and feature selection are combined with prior knowledge in the research methodology. A linear model, a radial basis function...

In this paper the performance of static and adaptive models for short-term natural gas load forecasting has been investigated. The study is based on two sets of data, i.e. natural gas consumption data for an individual model house, and natural gas consumption data for a local distribution...