Abstract: This project report emphasis enhancement of power quality by using UPQC with fuzzy logic controller (FLC), Artificial Neural Network (ANN) controller and with the conventional proportionalintegral (PI) controller. The unified power quality conditioner (UPQC) is being used as a universal active power conditioning device to mitigate both current and voltage harmonics at a distribution s...

In this paper, an adaptive attitude control algorithm is developed based on neural network for a satellite using four reaction wheels in a tetrahedron configuration. Then, an attitude control based on feedback linearization control is designed and uncertainties in the moment of inertia matrix and disturbances torque have been considered. In order to eliminate the effect of these uncertainties, ...

In this paper an Artificial Neural Network (ANN) based controller is presented for the Automatic Generation Control (AGC) of a five area interconnected power system with reheat turbines. The control scheme guarantees that steady state error of the area frequencies and inadvertent interchange of tielines are maintained in a given tolerance limit. ANN controller controls the inputs of each area i...

In this paper, we address the problem of adaptive neural control for a class of multi-input multi-output (MIMO) nonlinear time-delay systems in block-triangular form. Based on a neural network (NN) online approximation model, a novel adaptive neural controller is obtained by constructing a novel quadratictype Lyapunov–Krasovskii functional, which not only efficiently avoids the controller singu...

In this paper, the author proposes a sensorless direct torque control (DTC) of an induction motor (IM) fed by seven-level NPC inverter using artificial neural networks (ANN) and fuzzy logic controller. Fuzzy PI controller is used for controlling the rotor speed and ANN applied in switching select stator voltage. The control method proposed in this paper can reduce the torque, stator flux and to...

In recent years, soft computing methods, like fuzzy logic and neural networks have been  presented and developed for the purpose of mobile robot trajectory tracking. In this paper we will present a fuzzy approach to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions an...

During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the ...

In this paper, an adaptive fuzzy neural network (FNN) controller is proposed for missile guidance. The objective is for one defending missile (DM) to intercept an attacking missile (AM) in air battle scenario. The adaptive FNN controller is adopted to force the DM toward the AM under the existence of disturbance, and a monitoring controller is also designed to reduce the error between FNN contr...

In this paper, MLP network with sliding-mode controller and neural control is designed to the joint position control of two-link robot manipulators for periodic motion and predefined trajectory tracking control. Because the nonlinear nature robot, first the nonlinear and robust method sliding mode as a control theory for the system is chosen. Chattering phenomenon is always a problem of sliding...