Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability.This study proposes a novel approach for designing a fractional order proportional-integral-...Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability.This study proposes a novel approach for designing a fractional order proportional-integral-derivative(FOPID)controller that utilizes a modified elite opposition-based artificial hummingbird algorithm(m-AHA)for optimal parameter tuning.Our approach outperforms existing optimization techniques on benchmark functions,and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision.Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and reliability.We highlight the significance of our findings by demonstrating how our approach can improve the performance,safety,and reliability of autonomous vehicles.This study’s contributions are particularly relevant in the context of the growing demand for autonomous vehicles and the need for advanced control techniques to ensure their safe operation.Our research provides a promising avenue for further research and development in this area.展开更多
Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscil...Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.展开更多
This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and F...This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and Fractional Order PID(FOPID)controllers at the edge of an industrial network for Switched Reluctance Motor(SRM)speed control and torque ripple reduction.These techniques present notable advantages in terms of faster convergence and reduced computational complexity compared to existing optimization methods.Our research employs PID and FOPID controllers to regulate the speed and torque of the SRM,with a comparative analysis of other optimization approaches.In the domain of SRM control,we highlight the significance of the hysteresis band block in mitigating sudden state transitions,especially crucial for ensuring stable operation in the presence of noisy or slightly variable input signals requiring precise control.The results underscore the superior performance of the proposed optimization strategies,particularly showcasing the DBO-based cascaded PID and FOPID controllers,which exhibit reduced torque and current ripples along with improved speed response.Our investigation encompasses diverse loading conditions and is substantiated through time-domain simulations performed using MATLAB/SIMULINK.展开更多
The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this work.Interval uncertaint...The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this work.Interval uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world plants.Also,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)controller.To the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time delay.The three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction.Finally,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.展开更多
In this paper,three tuning methods of the integer order proportional integral derivative(IOPID)controller,the fuzzy proportional integral derivative(FPID)controller and the fractional order proportional integral deriv...In this paper,three tuning methods of the integer order proportional integral derivative(IOPID)controller,the fuzzy proportional integral derivative(FPID)controller and the fractional order proportional integral derivative(FOPID)controller for high order system are presented respectively.Both IOPID controller and FOPID controller designed by the two tuning methods can satisfy all the three specifications proposed,which can guarantee the desired control performance and the robustness of the high order system to the loop gain variations.From the simulation results,the three controllers meet the dynamic performance requirements of high order system.Moreover,the FOPID controller,with the shortest overshoot and adjustment time,outperforms the IOPID controller and the FPID controller for the high order system.展开更多
Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of...Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of the ECV.The overall structure and mathematical model of the SBW system are described at length.The fractional order proportional-integral-derivative(FOPID)controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system.The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation.Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error(ITAE),peak overshoot,as well as settling time.The time-domain simulations are implemented to identify the performance of the raised FOPID controller.The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative(PID)controller on the part of transient response,tracking capability and robustness.展开更多
In this paper, a fractional order proportional integral derivative （FOPID） controller for multiarea automatic generation control （AGC） scheme has been designed. FOPID controller has five parameters and provides tw...In this paper, a fractional order proportional integral derivative （FOPID） controller for multiarea automatic generation control （AGC） scheme has been designed. FOPID controller has five parameters and provides two additional degrees of flexibility in comparison to a proportional integral derivative （PID） controller. The optimal values of parameters of FOPID controller have been determined using Big Bang Big Crunch （BBBC） search algorithm. The designed controller regulates real power output of generators to achieve the best dynamic response of frequency and tie-line power on a load perturbation. The complete scheme for designing of the controllers has been developed and demonstrated on multiarea deregulated power system. The performance of the designed FOPID controllers has been compared with the optimally tuned PID controllers. It is observed from the results that the FOPID controller shows a considerable improvement in the performance as compared to the conventional PID controller.展开更多
本文研究了在FOPID控制器控制下的广义Van Der Pol随机系统瞬态概率密度函数和可靠性函数变化情况.首先,引入广义谐和函数,将快变变量转换为慢变变量,并利用分数阶微积分的性质,获得了FOPID控制器在慢变变量形式下的新表达式.在此基础上...本文研究了在FOPID控制器控制下的广义Van Der Pol随机系统瞬态概率密度函数和可靠性函数变化情况.首先,引入广义谐和函数,将快变变量转换为慢变变量,并利用分数阶微积分的性质,获得了FOPID控制器在慢变变量形式下的新表达式.在此基础上,由于径向基神经网络具有准确性高,易于求解高维问题,求解速度快等优势,所以我们应用径向基神经网络分别对该随机系统所满足的前向和后向柯尔莫哥洛夫方程进行求解,得到随机系统的瞬态概率密度函数和可靠性函数.最后,通过分析控制器中分数阶导数和分数阶积分对Van Der Pol随机系统响应和可靠性的影响,我们得到结论,分数阶控制器一定程度上会增强系统的响应,并导致分岔.展开更多
应用于孤岛型微电网以实现频率控制功能的传统控制器多为分数阶PID(fractional order PID,FOPID)控制器及模糊分数阶PID(fuzzy fractional order PID,FFOPID)控制器,二者的控制性能均存在局限性。针对这一问题,设计了一种变论域混合FFO...应用于孤岛型微电网以实现频率控制功能的传统控制器多为分数阶PID(fractional order PID,FOPID)控制器及模糊分数阶PID(fuzzy fractional order PID,FFOPID)控制器,二者的控制性能均存在局限性。针对这一问题,设计了一种变论域混合FFOPID控制器,用于提高孤岛微电网的频率控制性能。通过对比FOPID、FFOPID以及变论域混合FFOPID3种控制器作用时的不同效果,证明了变论域混合FFOPID控制器相比其他控制器对于孤岛微电网的频率控制有着更好的控制性能。同时考虑了反馈信号受到测量噪声干扰时对控制器的控制性能产生影响进而使得孤岛微电网频率波动增大的情况,并针对此问题使用了动态数据校正(dynamic datareconciliation,DDR)滤波技术。通过对比时域仿真中FOPID、FFOPID以及变论域混合FFOPID控制器各自作用时孤岛微电网频率偏差的输出结果,验证了DDR滤波技术对孤岛微电网的频率控制的显著效果。展开更多
This paper delves into the parameter tuning of fractional-order PID(FOPID)controllers.FOPID controllers,with additional integral and derivative orders compared to traditional PID controllers,possess enhanced capabilit...This paper delves into the parameter tuning of fractional-order PID(FOPID)controllers.FOPID controllers,with additional integral and derivative orders compared to traditional PID controllers,possess enhanced capabilities in handling complex systems.However,effective tuning of its five parameters is challenging.To address this,multiple intelligent algorithms are investigated.The improved sparrow search algorithm(ISSA)utilizes Chebyshev chaotic mapping initialization,adaptive t-distribution,and the firefly algorithm to overcome the limitations of the basic algorithm,showing high accuracy,speed,and robustness in multi-modal problems.The grey wolf optimizer(GWO),inspired by the hunting behavior of grey wolves,has procedures for encircling,hunting,and attacking but may encounter local optima,and several improvement methods have been proposed.The genetic algorithm,based on the survival of the fittest principle,involves encoding,decoding,and other operations.Taking vehicle ABS control as an example,the genetic algorithm-based FOPID controller outperforms the traditional PID controller.In conclusion,different algorithms have their own advantages in FOPID parameter tuning,and the selection depends on system characteristics and control requirements.Future research can focus on further algorithm improvement and hybrid methods to achieve better control performance,providing a valuable reference for FOPID applications in industry.展开更多
文摘Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability.This study proposes a novel approach for designing a fractional order proportional-integral-derivative(FOPID)controller that utilizes a modified elite opposition-based artificial hummingbird algorithm(m-AHA)for optimal parameter tuning.Our approach outperforms existing optimization techniques on benchmark functions,and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision.Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and reliability.We highlight the significance of our findings by demonstrating how our approach can improve the performance,safety,and reliability of autonomous vehicles.This study’s contributions are particularly relevant in the context of the growing demand for autonomous vehicles and the need for advanced control techniques to ensure their safe operation.Our research provides a promising avenue for further research and development in this area.
文摘Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.
文摘This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and Fractional Order PID(FOPID)controllers at the edge of an industrial network for Switched Reluctance Motor(SRM)speed control and torque ripple reduction.These techniques present notable advantages in terms of faster convergence and reduced computational complexity compared to existing optimization methods.Our research employs PID and FOPID controllers to regulate the speed and torque of the SRM,with a comparative analysis of other optimization approaches.In the domain of SRM control,we highlight the significance of the hysteresis band block in mitigating sudden state transitions,especially crucial for ensuring stable operation in the presence of noisy or slightly variable input signals requiring precise control.The results underscore the superior performance of the proposed optimization strategies,particularly showcasing the DBO-based cascaded PID and FOPID controllers,which exhibit reduced torque and current ripples along with improved speed response.Our investigation encompasses diverse loading conditions and is substantiated through time-domain simulations performed using MATLAB/SIMULINK.
基金supported by the Estonian Research Council(PRG658)。
文摘The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this work.Interval uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world plants.Also,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)controller.To the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time delay.The three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction.Finally,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.
基金Sponsored by the Foundation of Jilin Educational Committee(Grant No.22201-2221010195)
文摘In this paper,three tuning methods of the integer order proportional integral derivative(IOPID)controller,the fuzzy proportional integral derivative(FPID)controller and the fractional order proportional integral derivative(FOPID)controller for high order system are presented respectively.Both IOPID controller and FOPID controller designed by the two tuning methods can satisfy all the three specifications proposed,which can guarantee the desired control performance and the robustness of the high order system to the loop gain variations.From the simulation results,the three controllers meet the dynamic performance requirements of high order system.Moreover,the FOPID controller,with the shortest overshoot and adjustment time,outperforms the IOPID controller and the FPID controller for the high order system.
基金Supported by National Natural Science Foundation of China （61273260）, Specialized Research Fund for the Doctoral Program of Higher Education of China （20121333120010）, Natural Scientific Research Foundation of the Higher Education Institutions of Hebei Province （2010t65）, the Major Program of the National Natural Science Foundation of China （61290322）, Foundation of Key Labora- tory of System Control and Information Processing, Ministry of Education （SCIP2012008）, and Science and Technology Research and Development Plan of Qinhuangdao City （2012021A041）
基金Project(2016YFC0802904)supported by the National Key Research and Development Program of China
文摘Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of the ECV.The overall structure and mathematical model of the SBW system are described at length.The fractional order proportional-integral-derivative(FOPID)controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system.The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation.Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error(ITAE),peak overshoot,as well as settling time.The time-domain simulations are implemented to identify the performance of the raised FOPID controller.The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative(PID)controller on the part of transient response,tracking capability and robustness.
文摘In this paper, a fractional order proportional integral derivative （FOPID） controller for multiarea automatic generation control （AGC） scheme has been designed. FOPID controller has five parameters and provides two additional degrees of flexibility in comparison to a proportional integral derivative （PID） controller. The optimal values of parameters of FOPID controller have been determined using Big Bang Big Crunch （BBBC） search algorithm. The designed controller regulates real power output of generators to achieve the best dynamic response of frequency and tie-line power on a load perturbation. The complete scheme for designing of the controllers has been developed and demonstrated on multiarea deregulated power system. The performance of the designed FOPID controllers has been compared with the optimally tuned PID controllers. It is observed from the results that the FOPID controller shows a considerable improvement in the performance as compared to the conventional PID controller.
文摘本文研究了在FOPID控制器控制下的广义Van Der Pol随机系统瞬态概率密度函数和可靠性函数变化情况.首先,引入广义谐和函数,将快变变量转换为慢变变量,并利用分数阶微积分的性质,获得了FOPID控制器在慢变变量形式下的新表达式.在此基础上,由于径向基神经网络具有准确性高,易于求解高维问题,求解速度快等优势,所以我们应用径向基神经网络分别对该随机系统所满足的前向和后向柯尔莫哥洛夫方程进行求解,得到随机系统的瞬态概率密度函数和可靠性函数.最后,通过分析控制器中分数阶导数和分数阶积分对Van Der Pol随机系统响应和可靠性的影响,我们得到结论,分数阶控制器一定程度上会增强系统的响应,并导致分岔.
文摘应用于孤岛型微电网以实现频率控制功能的传统控制器多为分数阶PID(fractional order PID,FOPID)控制器及模糊分数阶PID(fuzzy fractional order PID,FFOPID)控制器,二者的控制性能均存在局限性。针对这一问题,设计了一种变论域混合FFOPID控制器,用于提高孤岛微电网的频率控制性能。通过对比FOPID、FFOPID以及变论域混合FFOPID3种控制器作用时的不同效果,证明了变论域混合FFOPID控制器相比其他控制器对于孤岛微电网的频率控制有着更好的控制性能。同时考虑了反馈信号受到测量噪声干扰时对控制器的控制性能产生影响进而使得孤岛微电网频率波动增大的情况,并针对此问题使用了动态数据校正(dynamic datareconciliation,DDR)滤波技术。通过对比时域仿真中FOPID、FFOPID以及变论域混合FFOPID控制器各自作用时孤岛微电网频率偏差的输出结果,验证了DDR滤波技术对孤岛微电网的频率控制的显著效果。
文摘This paper delves into the parameter tuning of fractional-order PID(FOPID)controllers.FOPID controllers,with additional integral and derivative orders compared to traditional PID controllers,possess enhanced capabilities in handling complex systems.However,effective tuning of its five parameters is challenging.To address this,multiple intelligent algorithms are investigated.The improved sparrow search algorithm(ISSA)utilizes Chebyshev chaotic mapping initialization,adaptive t-distribution,and the firefly algorithm to overcome the limitations of the basic algorithm,showing high accuracy,speed,and robustness in multi-modal problems.The grey wolf optimizer(GWO),inspired by the hunting behavior of grey wolves,has procedures for encircling,hunting,and attacking but may encounter local optima,and several improvement methods have been proposed.The genetic algorithm,based on the survival of the fittest principle,involves encoding,decoding,and other operations.Taking vehicle ABS control as an example,the genetic algorithm-based FOPID controller outperforms the traditional PID controller.In conclusion,different algorithms have their own advantages in FOPID parameter tuning,and the selection depends on system characteristics and control requirements.Future research can focus on further algorithm improvement and hybrid methods to achieve better control performance,providing a valuable reference for FOPID applications in industry.
