TOWARDS IMPROVED AUTOMATION FOR DESALINATION PROCESSES .2. INTELLIGENT CONTROL

The frontiers of automatic control are expanding to keep abreast of th e state-of-the-art technology. Innovative concepts in control systems have relegated what was considered a satisfactory solution a decade ag o 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 beco ming almost commonplace worldwide incorporating special features such as expert systems, self-tuning, self-diagnosis, life management, equip ment health monitoring, modelling and simulation. Thus, a trend toward s larger desalination plants necessitates more sophisticated automatio n technology. In view of the benefits that can be realized from the ap plication of artificial intelligence in the control field of desalinat ion 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 in telligent control is necessary due to computational complexity, nonlin ear behaviour with many degrees of freedom, and the presence of uncert ainty in control environment. Intelligent control can be used at diffe rent levels of control systems. On the highest level, monitoring of da ta, selection of algorithms, selection of objective functions, and ass igning of values for the setpoints are the main aims. On the level of advanced regulatory control, process identification can be supported b y intelligent control, e,g. selecting of structures by expert systems, implementing neural networks for parameter estimation etc. Expert sys tems, assisted by pattern recognition, can be used at this level for t uning of adaptive controllers. Adaptation of controller parameters acc ording to an intelligent strategy can also be provided by neural netwo rks. Also, expert systems can be used to assist the design of advanced control systems. In the large field of design of conventional control systems, artificial intelligence methods can be used to provide intel ligent user interface, to select the best algorithms, to consider desi gn heuristics for optimization of feedback control loops etc. The vary ing and uncertain conditions in a multistage flash (MSF) desalination plant during its operation in the annual cycle of seasons under differ ent situations of loads and disturbances, point out that no single fix ed strategy, no matter how advanced it may be, is likely to be either valid or possible at all times under all conditions in all the sub-sys tems related to the plant. This paper is addressed to some aspects of artificial intelligence (AI) which aims at equipping the process with the capability for continual analysis and assessment of the situations that arise during the course of operation of the plant leading to the choice and implementation of an appropriate course of action in proce ss control. At the outset MSF plant conditions calling for considerati on of advanced control strategies with AI support are highlighted. The n some aspects of AI applicable to plant control are reviewed, finally , suggestions towards intelligent control of MSF plants are made point ing also to the possibility of an integrated system for Process Contro l and Care.