A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect ...

reducing the number of colors in an image while preserving its quality, is of importance in many applications such as image analysis and compression. it also decreases memory and transmission bandwidth requirements. moreover, classification of image colors is applicable in image segmentation and object detection and separation, as well as producing pseudo-color images. in this paper, the kohene...

This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model of the process, then another network is trained to act as a combined state and parameter estimator for t...

An adaptive sliding mode control (ASMC) based on improved linear extended state observer (LESO) is proposed for nonlinear systems with unknown and uncertain dynamics. LESO designed to estimate total disturbance of the system, an interval type-2 fuzzy neural network (IT2FNN) used optimize approximate observe bandwidth LESO, parameter tuning realized gradient descent (GD) method. Based estimated ...

This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...

e-mail. [email protected] Abstract A nonlinear observer for a general class of singleoutput nonlinear systems is proposed based on a generalized Dynamic Recurrent Neural Network (DRNN). The Neural Network (NN) weights in the observer are tuned on-line, with no off-line learning phase required. The observer stability and boundness of the state estimates and NN weights are proven. No exact knowle...

Lightweight concrete (LWC) is a kind of concrete that made of lightweight aggregates or gas bubbles. These aggregates could be natural or artificial, and expanded polystyrene (EPS) lightweight concrete is the most interesting lightweight concrete and has good mechanical properties. Bulk density of this kind of concrete is between 300-2000 kg/m3. In this paper flexural strength of EPS is modeled...

This paper presents an adaptive neural network output feedback controller for a class of uncertain SISO nonlinear non-affine systems. Since the system states are not required to be available for measurement, an observer is designed to estimate the system states. Comparing to existing results, this method does not require a priori knowledge about the sign of control gain direction. To deal with ...