Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays...Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.展开更多
In order to meet the precision requirements and tracking performance of the continuous rotary motor electro-hydraulic servo system under unknown strong non-linear and uncertain strong disturbance factors,such as dynam...In order to meet the precision requirements and tracking performance of the continuous rotary motor electro-hydraulic servo system under unknown strong non-linear and uncertain strong disturbance factors,such as dynamic uncertainty and parameter perturbation,an improved active disturbance rejection control(ADRC)strategy was proposed.The state space model of the fifth order closed-loop system was established based on the principle of valve-controlled hydraulic motor.Then the three parts of ADRC were improved by parameter perturbation and external disturbance;the fast tracking differentiator was introduced into linear and non-linear combinations;the nonlinear state error feedback was proposed using synovial control;the extended state observer was determined by nonlinear compensation.In addition,the grey wolf algorithm was used to set the parameters of the three parts.The simulation and experimental results show that the improved ADRC can realize the system frequency 12 Hz when the tracking accuracy and response speed meet the requirements of double ten indexes,which lay foundation for the motor application.展开更多
文摘Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.
基金Project(51975164)supported by the National Natural Science Foundation of ChinaProject(2019-KYYWF-0205)supported by the Fundamental Research Foundation for Universities of Heilongjiang Province,China。
文摘In order to meet the precision requirements and tracking performance of the continuous rotary motor electro-hydraulic servo system under unknown strong non-linear and uncertain strong disturbance factors,such as dynamic uncertainty and parameter perturbation,an improved active disturbance rejection control(ADRC)strategy was proposed.The state space model of the fifth order closed-loop system was established based on the principle of valve-controlled hydraulic motor.Then the three parts of ADRC were improved by parameter perturbation and external disturbance;the fast tracking differentiator was introduced into linear and non-linear combinations;the nonlinear state error feedback was proposed using synovial control;the extended state observer was determined by nonlinear compensation.In addition,the grey wolf algorithm was used to set the parameters of the three parts.The simulation and experimental results show that the improved ADRC can realize the system frequency 12 Hz when the tracking accuracy and response speed meet the requirements of double ten indexes,which lay foundation for the motor application.
