Event-based intelligent control of saturated chemical plant using endomorphic neural network model

An event-based control system with an endomorphic neural network model is designed and realized to control a saturated nonlinear plant. This scheme is based on an event-based control paradigm. However, this scheme has some aspects different from the original scheme due to the saturation property of the plant. This new scheme may be viewed as a method combining a time-based diagnosis mechanism in event-based control with a state-based control mechanism in neural network control. A chemical plant having strong nonlinearity and complicated dynamics is controlled using the realized event-based control system. This paper discusses the structure of an event-based controller, the neural network modelling methodology, related problems, and experimental results