In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...

An innovative adaptive control method for speed control of induction motor based on field oriented control is presented in this paper. The fusion of sliding-mode and type-2 neuro fuzzy systems is used to control this system. An online learning algorithm based on sliding-mode training algorithm, and type-2 fuzzy systems is employed to deal with parametric uncertainties and disturbances, by adjus...

In this paper, the goal is the improvement of transient condition in a single machine system with designing of the nonlinear controllers for static Synchronous Compensator (STATCOM). By obtaining the Lyapunov function in presence of compensator in the system, some controllers are designed for it which by satisfying the Lyapunov stability criteria will increase the margin of transient stability ...

this paper presents the approach of neuro fuzzy systems to design autonomous vehicle control system. The purposed intelligent controller deliberates obstacles avoidance, unstructured environment adaptation and speed scheduling of autonomous vehicle based on neuro-fuzzy with reinforcement learning mechanism. The purposed system provides the autonomous vehicle navigation and speed control in unst...

A neuro fuzzy control algorithm for planar robotic manipulators is developed in this paper. This control algorithm is able to handle uncertainties, disturbances or unmodeled dynamics. Asymptotic stability of the equilibrium state of the control system is shown by use of direct Lyapunov method and Barbalat’s Lemma. A series of simulations confirms the algorithm goodness. Key-Words: fuzzy control...

This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required modelling rules from input/output measurements recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the on-line parameter lea...

This paper proposes a Single Input Neuro-fuzzy Logic Controller based on Radial Basis Function Network (SI-NFRBFN) for non-linear systems. To obtain single input from multi inputs a Distance Method is suggested. Using this method all the uncertain inputs are simplified into a single input known as distance. With the help of this variable the control unit matrix introduced in Hybrid Neuro-fuzzy ...

Abstract: An adaptive identifier for neuro-fuzzy control system nonlinear dynamic object operating in conditions of uncertainty intrinsic properties and the environment. The algorithms of structural and parametric identification in real time are a combination of an identification algorithm coefficients of linear management and methods of the theory of interactive adaptation. Adaptive neuro-fuzz...

today, dc motors is still being used globally due to their easy speed controllability. in this article, an adaptive neuro-fuzzy inference system (anfis) controller is designed for dc motors. the main purpose of performing such task is to reduce the dc motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...