Fuzzy Regulator for Two-Phase Gas–Liquid Pipe Flows Control

The paper presents an intelligent module to control dynamic two-phase gas–liquid mixtures pipelines flow processes. The module is intelligent because it uses the algorithm based on AI methods, namely, fuzzy logic inference, to build the fuzzy regulator concept. The developed modification has allowed to design and implement the black-box type regulator. Therefore, it is not required to determine any of the complicated computer models of the flow rig, which is unfortunately necessary when using the classic regulators. The inputs of the regulator are four linguistic variables that are decomposed into two classes and two methods of fuzzification. The first input class describes the current values of gas and liquid pipe flows, which at the same time are the controlled values manipulated to generate desired flow type. The second class of the input signals contains a current flow state, namely, its name and the name preferred by the operator flow type. This approach improves the control accuracy since the given flow type can be generated with different gas and liquid volume fractions. Those values can be optimized by knowing the current flow type. Moreover, the fuzzification algorithm used for the input signals included in the first-class covers the current crisp signal value and its trend making the inference more accurate and resistant to slight measurement system inaccuracy. This approach of defined input signals in such environments is used for the first time. Considering all mentioned methods, it is possible to generate the desired flow type by manipulating the system input signals by minimum required values. Furthermore, a flow type can be changed by adjusting only one of the input signals. As an output of the inference process, two linguistic values are received, which are fuzzified adjustment values of the liquid pump and gas flow meter. The regulator looks to be universal, and it can be adopted by multiple test and production rigs. Moreover, once configured with a dedicated rig, it can be easily operated by the non (domain) technical staff. The usage of fuzzy terms makes understanding both the control strategy working principles and the obtained results easy.

DESIGN AND MODELING OF ANFIS REGULATOR TO COMPENSATE DEVIATIONS OF MOBILE PLATFORM OF PARALLEL CABLE-DRIVEN ROBOT

The article deals with a description of design and modeling of neuro-fuzzy regulator (ANFIS) which provides a compensation of deviations of mobile platform of parallel cable-driven robot. The regulator uses adjusting of lengths of unwounded cables. Evaluation of the control system has been made according to the quality criterion as an elongation of each cable comparatively to given values.

REGULACIJA TEMPERATURE KGH SISTEMA UPOTREBOM PI-LIKE FUZZY REGULATORA I GA

Osnovni zadatak ovog rada jeste regulacija temperature KGH sistema, a da se pri tom ne naruše zahtevani radni uslovi. Korišćen je PI-like fuzzy regulator, koji upravlja ventilom za dovod hladne vode na izmenjivač toplote KGH sistema. Izvršena je optimizacija fuzzy tabele pravila pomoću genetskih algoritama.