TOWARDS IMPROVED AUTOMATION FOR DESALINATION PROCESSES .2. INTELLIGENT CONTROL

作     者：RAO, GP ALGOBAISI, DMK HASSAN, A KURDALI, A BORSANI, R AZIZ, M 

作者机构：WATER & ELECT DEPTABU DHABIU ARAB EMIRATES IRITECNADEPT DESALINATGENOAITALY 

出 版 物：《DESALINATION》 (脱盐)

年 卷 期：1994年第97卷第1-3期

页      面：507-528页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0815[工学-水利工程] 

主　　题：Desalination 

摘      要：The frontiers of automatic control are expanding to keep abreast of the state-of-the-art technology. Innovative concepts in control systems have relegated what was considered a satisfactory solution a decade ago to obsolescence today, One novel feature is artificial intelligence (AI) which has ability to cope with uncertainties that we encounter in today s complex process control. Intelligent control systems are becoming almost commonplace worldwide incorporating special features such as expert systems, self-tuning, self-diagnosis, life management, equipment health monitoring, modelling and simulation. Thus, a trend towards larger desalination plants necessitates more sophisticated automation technology. In view of the benefits that can be realized from the application of artificial intelligence in the control field of desalination processes, intelligent control is the application of AI in control, employing methods like expert systems, neural networks, fuzzy logic and pattern recognition. Thereby, learning and decision making are the most important features of intelligent control, The application of intelligent control is necessary due to computational complexity, nonlinear behaviour with many degrees of freedom, and the presence of uncertainty in control environment. Intelligent control can be used at different levels of control systems. On the highest level, monitoring of data, selection of algorithms, selection of objective functions, and assigning of values for the setpoints are the main aims. On the level of advanced regulatory control, process identification can be supported by intelligent control, e,g. selecting of structures by expert systems, implementing neural networks for parameter estimation etc. Expert systems, assisted by pattern recognition, can be used at this level for tuning of adaptive controllers. Adaptation of controller parameters according to an intelligent strategy can also be provided by neural networks. Also, expert systems can be used to