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Problem statement:The surge phenomenon in the centrifugal compressor, the nonlinearities and uncertainties of the compression system make it impossible to use a conventional controller over a wide range of operation. Approach: A new dual fuzzy controller for nonlinear model of compression system was proposed in this study. This fuzzy controller was designed that consisted of active surge control and phase control without any explicit system models, but driven in human thinking mechanism. Results: Simulation example of compression system was given to demonstrate the validity of proposed control scheme. It was shown that fuzzy controller can be simplified and good tracking control performance can be achieved by choosing appropriate fuzzy roles. But, the dual fuzzy controller can successfully intervene in control surge of compression system. Conclusion: This new fuzzy control methodology suggested in this study reproduced well main characteristics of turbo compressor dynamic model developed by Moore and Gretzer and give place to a more precise and easy to handle representation. It is about an inaccuracies reproducing with a certain degree of satisfaction of real process without being as much complex.

The purpose of this work is to increase the online availability of industrial gas compression installations. By prevention against the failures in gas turbines, used in this gas compression installation. In this work a new vibrations supervision approach based on parity space is used, this will guarantee us the optimal availability of this system. The obtained results show clearly how to ensure a reliable and safe operation in gas compression plants to economically recover the transported gas.

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The diagnoses in industrial systems represent an important economic objective in process industrial automation area. To guarantee the safety and the continuity in production exploitation and to record the useful events with the feedback experience for the curative maintenance. We propose in this work to examine and illustrate the application ability of the spectral analysis approach, in the area of fault detection and isolation industrial systems. In this work, we use a combined analysis diagram of time-frequency, in order to make this approach exploitable in the proposed supervision strategy with decision making module. The obtained results, show clearly how to guarantee a reliable and sure exploitation in industrial system, thus allowing better performances at the time of its exploitation on the supervision strategy.

During the gas turbine exploitation the presence of small defects can cause very high vibration amplifications, localized on the components of this rotating machine. For this, a diagnostic process is necessary for decision-making during the monitoring of failures caused by vibration phenomena, which consists in observing the system by comparing its current data with the data coming from a normal operation. These indicators help engineer to determine the symptoms for the failing components of the system. This work deals with problems related to these vibrations, with the aim of developing a system of detection of failures using dynamic neural networks approach. The originality of this contribution is to calculate the various alarms based on this system which used the determined vibration models in order to ensure a reliable and safe operation of the gas compression installation using the examined gas turbine.