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Process Control Of A Laboratory Combustor Using Neural Networks, Thana Slanvetpan

Dissertations

Active feedback and feedforward-feedback control systems based on static-trained feedforward multi-layer-perceptron (FMLP) neural networks were designed and demonstrated, by experiment and simulation, for selected species from a laboratory two stage combustor. These virtual controllers functioned through a Visual Basic platform. A proportional neural network controller (PNNC) was developed for a monotonic control problem - the variation of outlet oxygen level with overall equivalence ratio (Φ₀). The FMLP neural network maps the control variable to the manipulated variable. This information is in turn transferred to a proportional controller, through the variable control bias value. The proposed feedback control methodology …