Several scientific forecasting models for presidential elections have been suggested. However, most of these models are based on traditional statistics approaches. Since the system is linguistic, vague, and dynamic in nature, the traditional rigorous mathematical approaches are inappropriate for the modeling of this kind of humanistic system. This paper presents a combined neural fuzzy approach...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

In this paper, a novel adaptive fuzzy backstepping output feedback control scheme is proposed for a class of single-input single-output (SISO) uncertain nonlinear systems without measurements of states. Fuzzy logic systems (FLS) are used to tackle unknown nonlinear functions, and the adaptive fuzzy output feedback controller is constructed by combining fuzzy filters observer design and the dyna...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

This paper shows how adaptive systems can learn to add an optimal amount of noise to some nonlinear feedback systems. Noise can improve the signal-to-noise ratio of many nonlinear dynamical systems. This “stochastic resonance” (SR) effect occurs in a wide range of physical and biological systems. The SR effect may also occur in engineering systems in signal processing, communications, and contr...

This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...

a novel technique is investigated for pid controller adaptation in order to control thetemperature of a liquid-phase reactor tank by using a heat exchanger system. as for nonlinearity,time delay problems and model uncertainties introduced by the heat exchanger, an interval type-2fuzzy system (it2fs) is implemented to enhance and improve the total control performance.moreover, the fuzzy inferenc...

A Petri net is an abstract formal model of the behavior of a system and information flow. The properties, concepts, and techniques of Petri net are so as to present it as a simple and strong method for describing and analyzing information flow and systems control. Fuzzy Petri Net (FPN) is an appropriate powerful model to emulate knowledge base systems using fuzzy rules. Yet, FPN model does not ...

This paper proposes a fuzzy approximation-based adaptive sliding-mode controller for uncertain nonlinear perturbed underactuated systems. The fuzzy logic system is used for approximating the unknown nonlinear functions. For estimating the parameters of the fuzzy systems and some unknown bounds, a set of adaptation laws are appropriately designed. The boundedness of all signals of the closed-loo...

In allusion to high electricity consumption and resource wasting of college schoolroom, this paper proposes a lighting fuzzy control system based on CC2430. The deviation and transformation rate comparing ideal illumination and the practical one has inferenced by Fuzzy Model Reference adaptive system (FMRAS), and it can compensate natural light illumination stabilizing schoolroom lighting throu...