For a class of uncertain nonlinear systems, this paper presents a method based on biological adaptation strategies of hybrid adaptive fuzzy control method. The method in the controller design, the ecological niche theory function as a consequent of the fuzzy rule fuzzy system, is established based on the biological adaptation of the adaptive controller. The controller design embodies the biolog...

This paper proposes inverse fuzzy-model-based feed-forward fuzzy controllers to compensate non-linear terms that affect the system dynamics. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows these controllers to be used in applications were the knowledge to control the process does not exist or the process is subject to changes in its dyn...

In this paper we presented an architecture and basic learning process underlying in fuzzy inference system and adaptive neuro fuzzy inference system which is a hybrid network implemented in framework of adaptive network. In real world computing environment, soft computing techniques including neural network, fuzzy logic algorithms have been widely used to derive an actual decision using given i...

the aim of this research is the assessment of the relation between rainfall and large scale synoptically patterns at khorasan razavi province. in this study, using adaptive neuro fuzzy inference system, the rainfall estimation has been done from april to june in the area under study. spring rainfall data including the information of 38 synoptic, climatologic and rain gauge stations from 1970 to...

In this study, an adaptive fuzzy sliding-mode control (AFSMC) system is adopted to control the position of an induction servo motor. The AFSMC system comprises the fuzzy control design and the robust control design. In the fuzzy control design a fuzzy controller is designed to mimic an ideal control law. In the robust control design a robust controller is designed to compensate the approximatio...

In this paper, an adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time delays and unmeasured states. By using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive state observer is designed for estimating the unmeasured states. By combining the adaptive backstepping technique with adaptive fuzzy control desi...

In this paper, an adaptive fuzzy backstepping output feedback control approach is proposed for a class of strict-feedback stochastic nonlinear systems with time delays and immeasurable states. Fuzzy logic systems are firstly utilized to approximate the unknown nonlinear functions, and then a fuzzy state observer is designed to estimate the immeasurable states. By combining the fuzzy adaptive co...

osting by E Abstract Direct adaptive fuzzy controller is a class of adaptive fuzzy controllers which use fuzzy logic system (FLS) as controller. Interval type-2 fuzzy sets are able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of fuzzy logic controller (FLC). In this paper, a direct adaptive interval type-2 FLC is proposed for controllin...

This paper presents the m e w of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-0 environment and is of particular importance for guidance, navigation, and control of flyi...

Motivated by the need to develop more effective methods of controlling uncertain non-linear systems, this paper focus on developing an adaptive fuzzy model-based controller, in which the optimisation variables remain in the fuzzy domain. The scheme uses an on-line fuzzy identification scheme, which is able to generate a fuzzy relational model using the training data from the system. The propose...