Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

s--By making the controller adaptive, ideal performance and granted stability of the closed loop system can be achieved for even a large change in system parameters. In the present study, adaptive controllers based on minimum variance, pole placement and linear quadratic techniques are investigated. The controller based on minimum variance is noise sensitive and actuator voltage changes sign af...

A novel controller based on adaptive controller and fuzzy controller for Permanent Magnet Direct Current motor is proposed in this paper. The proposed controller is compared with adaptive controller and fuzzy controller for PMDC motor. By means of simulation in MATLAB, we concluded that the proposed controller will be achieved the shorter settling time and also lower overshoot and steady state ...

This paper presents a robust control scheme for distributed generations (DGs) in islanded mode operation of a microgrid (MG). In this strategy, assuming a dynamic slack bus with constant voltage magnitude and phase angle, nonlinear equations of the MG are solved in the slack-voltage-oriented synchronous reference frame, and the instantaneous active and reactive power reference for the slack bus...

The objective of the model reference adaptive fuzzy control (MRAFC) is to change the rules definition in the direct fuzzy logic controller (FLC) and rule base table according to the comparison between the reference model output signal and system output. The MRAFC is composed by the fuzzy inverse model and a knowledge base modifier. Because of its improved algorithm, the MRAFC has fast learning ...

In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector and the vehicle. The controller creates proper configurations for the manipulator to prevent the robot from being overturned. The optimal configuration and thus the most favorable contr...

An alternative approach for intelligent tuning of a control loop will be presented in this paper. The objective is to design an algorithm which will tune the controller employing a neuro-fuzzy based algorithm. Structure and design method based on this approach will be explored, which include an adaptive network employed as building block, the backpropagation gradient method and least square est...

We present a tool to estimate the performance of the neural network in a neural network based adaptive controller. Using a Bayesian approach, this tool supports verification and validation of the adaptive controller as well as on-line monitoring. In this paper, we discuss our approach and present simulation results using the adaptive controller developed for NASA’s IFCS (Intelligent Flight Cont...

In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best...

in this paper, controlling the gyros with linear plus cubic damping is considered. hence, an adaptive control algorithm is proposed to overcome the uncertainties in model parameters and the chaotic behavior of gyroscopes. it is noted that for general applications dynamic model coefficient of gyros is not precisely determined, on the other hand, with respect to a particular coefficient gyroscope...