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Optimal Intelligent Control for HVAC Systems

Khooban M. H., Soltanpour M. R., Abadie D. N. M., Esfahani Z.

Journal of Power Technologies

2012

Vol. 92, nr 3

192--200

In this paper a novel Optimal Fuzzy Proportional-Integral-Derivative Controller (OFPIDC) is designed for controlling the air supply pressure of Heating, Ventilation and Air-Conditioning (HVAC) system. The parameters of input membership functions, output polynomial functions of first-order Sugeno, and PID controller coefficients are optimized simultaneously by random inertia weight Particle Swarm Optimization (RNW-PSO). Simulation results show the superiority of the proposed controller than similar non-optimal fuzzy controller.

Improvement of interpretation of dissolved gas analysis for power transformers.

Aragon-Patel J., Fischer M., Tenbohlen S.

Prace Naukowe Instytutu Podstaw Elektrotechniki i Elektrotechnologii Politechniki Wrocławskiej. Konferencje

2007

Vol. 46, nr 19

91-97

Assessment of power transformer conditions and lifespan has acquired crucial significance in latest years. Dissolved Gas Analysis (DGA) has proved to be useful for diagnostic of incipient and potential faults in power transformers. The first part of this paper deals with an experimental investigation carried out to study relation between gas generation and partial discharge. In the second part, a fuzzy logic based interpretation method (FL1), which is founded on fuzzy set theory is described and implemented as an improved DGA interpretation method that provides higher reliability and precision of fault diagnostics.

Influence of fuzzy predictor parameters on the prediction of the residual lifetime of electrical rotary machine insulation

Hammer M., Svoboda J., Szabo R., Riha Z., Latina P., Vavruska J.

Prace Naukowe Instytutu Podstaw Elektrotechniki i Elektrotechnologii Politechniki Wrocławskiej. Konferencje

2004

Vol. 40, nr 15

204--207

The contribution deals with the lifetime prediction of the Relanex insulating material used for the electrical rotary machine windings. By means of quantities Bv, Ba, Uk and utilizing the fuzzy apparatus in the form of fuzzy predictor, we determine the intensity of breakdown voltage and, consequently, the current state of the insulating material from the point of view of electric strength and the lifetime prediction of the material. To predict the breakdown voltage intensity, the fuzzy predictor of Sugeno type was used, particularly for easy setting of input parameters. According to the matrix of the values of individual inputs (Bv, Ba, Uk, Up) measured and the subsequent training phase, it is possible to predict the values of critical voltage Ups that can be further compared with real breakdown voltages Up and to make evaluations on the basis of relative and absolute errors.