Моделирование контроллера с нечеткой логикой для нелинейных и нестабильных систем управления

Али Хавалдех, Мохамед Махди, Монзер Кришан

Rule-based fuzzy control, in which the plant model is replaced by a number of control rules, provides an alternative approach and has been developed significantly. On the other hand, the potential benefits of neural networks extend beyond the high computation rates provided by the massive parallelism to provide a greater degree of robustness. integrating these two approaches brings what is so-called neurofuzzy system which gives rise to gain the merits of both approaches.

Structural and functional mapping from a fuzzy logic-based algorithm to the neural network-based approach has been considered with a thorough design procedures for SISO control systems.

Simulation technique will be implemented throughout this research using C++ programming language to verify the proposed controller capabilities.

Keywords: Functional Neurofuzzy Controller (FNFC), Multi-Layer Perceprtron Neural Networks (MLP NN)

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Али Хавалдех

Ali is a computer engineering working for Philadelphia University / Amman / Jordan.

He published about 12 scientific researches in the fields of electrical machines and soft computing.