Process Control System Identification - MOHAMED, MOHAMED ELSADIG (universiti teknologi petronas, 2005)
The main purpose of this project is to develop black-box models. That can introduce another modeling tool in process control system identification field. These models need to address process that is difficult or complex to model using the mathematical or empirical modeling approaches. The core activity for this project is to develop a model for chemical process (single loop pressure control) using blackbox identification techniques. This approach overcomes the difficulties that encountered in modeling processes that characterized with low level of a priori knowledge (operators have no priori knowledge about the system). Process control system identification is implemented through conducting an experiment on a gas /air pressure pilot plant where a set of input-output data are collected. Intelligent blackbox modeling techniques are implemented for building process model that can be utilized for further process control applications. Feedforward Neural network and fuzzy clustering method are used to obtain a model from the plant data. The author developed and compared the performance of black-box modeling techniques against the performance of empirical model. According to the comparison achieved. It is recommended to use black box modeling techniques for processes where process control engineers mayface the lackof knowledge about the system or the plant.