– This paper presents the optimization of a photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT). The optimization is suspended to reference optimal power. This optimization technique is developed to assure the optimum chopping ratio of buck-boost converter. The presented MPPT technique is used in photovoltaic water pumping system in order to optimize its e...

This paper presents neural network (NN) control of planar four-legged walking robot. The control system consists of a neural controller, standard PD controller and walking robot. Proposed NN is employed as an inverse controller of the robot. In addition to feedforward connections from the input layer to the hidden layer and from the hidden layer to the output layer, there is also feedback conne...

A novel approach to neural network based tracking-control of robot manipulator including actuator dynamics is proposed by using of backstepping method. A simple two-step backstepping is considered for an nlink robotic system, and a feedforward neural controller is designed at second step where structured and unstructured uncertainties in robot dynamics and actuator model are approximated by thi...

In this paper, the combination of RBF (Radial Basis Function) neural network and sliding mode control, which is used for vibration control, is examined. The approach is based on a sliding mode control methodology which drives the system towards a sliding surface by tuning the parameters of the controller using Gaussian radial basis function neural network. The input and output of RBF neural net...

this paper addresses a nonlinear observer based control scheme to synchronize chaotic systems subject to uncertainties and external disturbances. it is assumed that the dynamic of slave system is not completely known. in order to compensate for the system perturbation resulting from parameter variations and mismodeling phenomena, an adaptive neural network observer is employed to handle this pr...

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning...

This paper presents the design and implementation of neural network controller for reducing torque ripples in brushlessDC (BLDC) motor drive with trapezoidal back-emf. The performances of the proposed neural networkcontroller are compared with the corresponding fuzzy PI controller and conventional PI controller. Simulation results are used to show the abilities and shortcomings of the proposed ...

This paper is a straightforward application of NLq stability criteria to neural model based controller design. We discuss the design of a linear dynamic output feedback controller for a ball and beam system for which a neural state space model is identi ed. This is done by applying dynamic backpropagation, constrained by internal or I/O stability conditions for NLq systems. The performance of t...

A neural network (NN) based adaptive output feedback controller is proposed for a class of nonlinear systems. In this control scheme, the adaptive output feedback NN controller is proposed by using an observer to estimate the states of the system. The weights of the neural network can be adjusted in terms of Lyapnuov’s stability criterion. The proposed controller can be applied to nonlinear sys...