A novel technique of designing application specific defuzzification strategies with neural learning is presented. The proposed neural architecture considered as a universal defuzzification approximator is validated by showing the convergence when approximating several existing defuzzification strategies. The method is successfully tested with fuzzy controlled reverse driving of a model truck. T...

The majority of the research work on fuzzy PID controllers focuses on the conventional two-input PI or PD type controller proposed by Mamdani (1974). However, fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. This paper investigates different fuzzy PID controller structures, including the Mamdani-type cont...

Intelligent energy management has become one of the major research fields in electrical engineering. It constitutes an important tool for efficient planning and operation of power systems and its significance has been intensifying particularly, because of the recent movement towards open energy markets and the need to assure high standards on reliability. Hybrid neuro-fuzzy paradigms have recen...

This paper presents efficient models in the area of damage potential classification of seismic signals. After an earthquake, one of the most important actions that authorities must take is to inspect structures and estimate the degree of damages. The interest is obvious for several reasons such as public safety, economical recourses management and infrastructure. This approach provides a compar...

This work describe a fuzzy inference system to support a musculokeletal disorders diagnosis. The musculokeletal disorders refer to conditions the involve the nerves, tendours, muscles and supporting structures of the body. Nowadays it is observed a increasing in the number of occupational injures and illness. The linguistic variables and rules of the systems were associated to the disease sympt...

This paper presents a survey on the ex isting methods for the stability analysis of fuzzy control systems including both conventional Mamdani s rule based fuzzy controllers and Takagi Sugeno controllers The overview considers several approaches including input output stability frequency response methods Lyapunov techniques and qualitative methods The paper also sumarizes the new stability techn...