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Go to Editorial ManagerThe use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
The use of image communication has increased in recent years. In this approach, the encryption process is performed by hiding the processing steps of the wavelet transform. The attacker cannot obtain the original image unless processing steps are known. In this paper, the performance of three different hidden wavelet-based schemes are applied. First, hiding filter types encryption scheme (HFT), second, hiding wavelet packet tree encryption scheme (HWPT), lastly, by combining the previous two methods (HFTWPT). Several experiments are given to illustrate the performance of the proposed schemes.
This paper presents a novel control framework for robot manipulator path tracking based on the integration of artificial immune systems, fuzzy logic, and fractional-order PID control. The proposed Fuzzy-Immune Fractional-Order PID (FIFOPID) controller combines immune feedback mechanisms, fuzzy logic reasoning, and fractional-order control principles, with controller parameters optimized using the Clonal Selection Algorithm (CSA). The performance of the FIFOPID controller is evaluated and compared against a Fuzzy-Immune PID (FIPID) controller under identical conditions. Simulation results conducted in MATLAB 2014a with SIMULINK demonstrate that the optimal FIFOPID controller outperforms the FIPID controller in terms of path tracking accuracy and overall control performance, highlighting its potential as an effective approach for precise robotic manipulator control.
This paper considers the neural network based PID controller. The learning and generalization properties of neural network are utilized in improving the performance of a conventional PID controller. Two different schemes are introduced. Both schemes are studied and their performances are comparatively evaluated on an example for uncertain system.
Obstacle avoidance and path planning are from the most important problems in mobile robots, especially in unknown environment . In this paper, we proposed an approach for mobile robot navigation combining path planning and obstacle avoidance. Methods such as obstacle avoidance are inspired from the nature, and have been developed by fuzzy logic to train an intelligent robot in unknown environment. The model of the robot has two driving wheels and the linear velocity and azimuth of the two wheels are independently controlled using PID controller. Inputs are obtained from ultrasonic sensors mounted on it.
Interest in neural networks as an alternative to the conventional algorithmic techniques has grown rapidly in recent years. Noise removal or noise suppression is an important task in image processing. In general, the results of the noise removal have a strong influence on the quality of the following image processing techniques. In this paper, two feed forward NN schemes have been presented for impulsive noise removal. The computation is reduced by using an artificial image in training. Results of NN schemes show high performance especially when the ratio of impulsive noise in testing are the same or greater than that of training image. The presented schemes are used for grayscale and also for truecolor.
This paper deals with the modeling and control strategics of the motion of wheeled mobile robot. The model of the mobile robot has two driving wheels and the azimuth and velocity are dependently controlled by two PID controllers. The PID controller is one of the earliest and famous industrial controllers. It has many advantages: It is economic, simple easy to be tuned and robu.~t. The tuning of these controllers is governed by system nonlinearities and continuous parameter variations. lbis paper deals with the optimal design of a PID controller for path tracking of mobile robot by using genetic algorithms (GA). The designed controller is tested for different paths.
A five-phase two-motor drive system with a series connection of stator windings and decoupled dynamic control is considered in the present paper. The two-motor drive system is supplied from a single five-phase Space Vector Pulse Width Modulation (S VPWM) Voltage Source Inverter (VSI) and controlled using a vector control scheme, provided that the stator windings are connected in series with appropriate phase transposition. The concept has been developed under the assumption that the inverter voltages are controlled in the stationary dq-reference frame. A fuzzy logic-based speed controller has been constructed and used to drive the two-motor in this work. The two-motor system, inverter system, and fuzzy controller models are implemented and tested using Simulink/Matlab facilities. 1be presented results show the validity of the model to do well for the sake of speed control in wider different operating conditions.
In this paper, a second order Sliding Mode Controller (SMC), based on Super – Twisting algorithm, Fuzzy estimator and PID controller is presented for quarter vehicle active suspensions. Because of the chattering that appeared at the output of the system when using first order SMC, second order SMC is preferred. The proposed controller has been derived in order to achieve the convergence and the stability of the system that can improve the comfortable driving and vehicles safety against different road disturbances. The Artificial Bee Colony optimization method has been utilized to find the optimal values of the proposed controller parameters. The obtained results of the simulations have been verified the efficiency and the ability of the proposed control scheme to suppress the oscillations and give the stability of the suspension system in the presence of uncertainty and different road disturbances.