A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced eff...A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.展开更多
Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been w...Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.展开更多
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ...This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.展开更多
To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pur...To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.展开更多
An optimal control strategy is proposed to improve the fermentation titer,which combines the support vector machine(SVM)with real code genetic algorithm(RGA).A prediction model is established with SVM for penicillin f...An optimal control strategy is proposed to improve the fermentation titer,which combines the support vector machine(SVM)with real code genetic algorithm(RGA).A prediction model is established with SVM for penicillin fermentation processes,and it is used in RGA for fitting function.A control pattern is proposed to overcome the coupling problem of fermentation parameters,which describes the overall production condition.Experimental results show that the optimal control strategy improves the penicillin titer of the fermentation process by 22.88%,compared with the routine operation.展开更多
Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inp...Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural networks.In this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training RVFL.The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is analyzed.The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.展开更多
This paper proposes a method of using multi controllers to control supermaneuverable aircraft. A nonlinear dynamic inversion controller is used for supermaneuver. A gain scheduled controller is used for routine man...This paper proposes a method of using multi controllers to control supermaneuverable aircraft. A nonlinear dynamic inversion controller is used for supermaneuver. A gain scheduled controller is used for routine maneuver. A switch algorithm is designed to switch the controllers. The flight envelopes of the controllers are different but have a common area in which the controllers are switched from one to the other. In the common area, some special boundaries are selected to decide switch conditions. The controllers all use vector thrust for lower velocity maneuver control. Unlike the variation structure theory to use a single boundary, this paper uses two boundaries for switching between the two controllers. One boundary is used for switching from dynamic inversion to gain scheduling, while the other is used for switching from gain scheduling to dynamic inversion. This can effectively avoid the system vibration caused by switching repeatedly at a single boundary. The method is very easy for engineering. It can reduce the risk of design of the supermaneuverable aircraft.展开更多
This paper describes a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). In order to improve MCFC’s generating performance, prolong its life and guarantee safety, it must be co...This paper describes a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). In order to improve MCFC’s generating performance, prolong its life and guarantee safety, it must be controlled efficiently. First, the output voltage of an MCFC stack is identified by a least squares support vector machine (LS-SVM) method with radial basis function (RBF) kernel so as to implement nonlinear predictive control. And then, the optimal control sequences are obtained by applying genetic algorithm (GA). The model and controller have been realized in the MATLAB environment. Simulation results indicated that the proposed controller exhibits satisfying control effect.展开更多
This paper is concerned with two popular and powerful methods in electrical drive applications:fieldoriented control(FOC)and space vector modulation(SVM).The proposed FOC-SVM method is incorporated with a predictive c...This paper is concerned with two popular and powerful methods in electrical drive applications:fieldoriented control(FOC)and space vector modulation(SVM).The proposed FOC-SVM method is incorporated with a predictive current control(PCC)-based technique.The suggested method estimates the desirable electrical torque to track mechanical torque at a fixed speed operation of permanent magnet synchronous motor(PMSM).The estimated torque is used to calculate the reference current based on FOC.In order to improve the performance of the traditional SVM,a PCC method is established as a switching pattern modifier.Therefore,PCC-based SVM is employed to further minimize the torque ripples and transient response.The performance of the controller is evaluated in terms of torque and current ripple and transient response to step variations of the torque command.The proposed method has been verified with MATLAB-Simulink model.Simulation results confirm the ability of this technique in minimizing the torque and speed ripples and fixing switching frequency,simultaneously.However,it is sensitive to parameter changes.展开更多
This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generat...This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generator (SEIG). The aim of the developed control method is to automatically tune and optimize the scaling factors and the membership functions of the Fuzzy Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated voltage source PWM converters with a carrier-based Sinusoidal PWM modulation for both Generator- and Grid-side converters have been connected back to back between the generator terminals and utility grid via common DC link. The indirect vector control scheme is implemented to maintain balance between generated power and power supplied to the grid and maintain the terminal voltage of the generator and the DC bus voltage constant for variable rotor speed and load. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and also machine parameters mismatches. The proposed control scheme has improved the voltage regulation and the transient performance of the wave energy scheme over a wide range of operating conditions.展开更多
三电机卷绕系统是一个强耦合非线性时变系统,存在卷轴半径、转动惯量以及摩擦系数等时变参数,导致张力协同控制精度较低.为了提高卷绕系统模型准确度,实时优化张力协同控制系统的动态性能,提出一种基于改进鲸鱼算法优化的多核最小二乘...三电机卷绕系统是一个强耦合非线性时变系统,存在卷轴半径、转动惯量以及摩擦系数等时变参数,导致张力协同控制精度较低.为了提高卷绕系统模型准确度,实时优化张力协同控制系统的动态性能,提出一种基于改进鲸鱼算法优化的多核最小二乘支持向量机回归(multi-kernel least squares support vector regression prediction model based on an improved whale algorithm optimization,WOA-M-LSSVR)预测模型和基于纵横交叉优化算法(crisscross optimization algorithm,CSO)优化的模型预测张力协同控制系统.根据最小二乘支持向量机回归原理建立多核LSSVR回归模型,并使用改进的自适应鲸鱼算法进行离线优化,得到系统预测模型;根据建立的预测模型,构建自适应更新的模型预测控制器,引入纵横交叉优化算法实现优化求解,最大程度避免了求解陷入局部最优的情况,提高了张力控制系统的动态性能.通过仿真和实验分析,验证了所设计的张力协同控制系统具有良好的动态性能和鲁棒性.展开更多
文摘A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.
基金Supported by the Major State Basic Research Development Program of China(2012CB720500)the National Natural Science Foundation of China(Key Program:U1162202)+2 种基金the National Science Fund for Outstanding Young Scholars(61222303)the National Natural Science Foundation of China(61174118,21206037)Shanghai Leading Academic Discipline Project(B504)
文摘Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.
基金Supported by the National Natural Science Foundation of China(21076179)the National Basic Research Program of China(2012CB720500)
文摘This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection.
基金funded by the National Key Research and Development Program of China,grant number:2023YFF0615404.
文摘To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.
基金Supported by the National Natural Science Foundation of China（60704036）
文摘An optimal control strategy is proposed to improve the fermentation titer,which combines the support vector machine(SVM)with real code genetic algorithm(RGA).A prediction model is established with SVM for penicillin fermentation processes,and it is used in RGA for fitting function.A control pattern is proposed to overcome the coupling problem of fermentation parameters,which describes the overall production condition.Experimental results show that the optimal control strategy improves the penicillin titer of the fermentation process by 22.88%,compared with the routine operation.
基金supported by the Ministry of Science and Technology of China(2018AAA0101000,2017YFF0205306,WQ20141100198)the National Natural Science Foundation of China(91648117)。
文摘Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural networks.In this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training RVFL.The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is analyzed.The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.
文摘This paper proposes a method of using multi controllers to control supermaneuverable aircraft. A nonlinear dynamic inversion controller is used for supermaneuver. A gain scheduled controller is used for routine maneuver. A switch algorithm is designed to switch the controllers. The flight envelopes of the controllers are different but have a common area in which the controllers are switched from one to the other. In the common area, some special boundaries are selected to decide switch conditions. The controllers all use vector thrust for lower velocity maneuver control. Unlike the variation structure theory to use a single boundary, this paper uses two boundaries for switching between the two controllers. One boundary is used for switching from dynamic inversion to gain scheduling, while the other is used for switching from gain scheduling to dynamic inversion. This can effectively avoid the system vibration caused by switching repeatedly at a single boundary. The method is very easy for engineering. It can reduce the risk of design of the supermaneuverable aircraft.
基金Project (No. 2003 AA517020) supported by the Hi-Tech Researchand Development Program (863) of China
文摘This paper describes a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). In order to improve MCFC’s generating performance, prolong its life and guarantee safety, it must be controlled efficiently. First, the output voltage of an MCFC stack is identified by a least squares support vector machine (LS-SVM) method with radial basis function (RBF) kernel so as to implement nonlinear predictive control. And then, the optimal control sequences are obtained by applying genetic algorithm (GA). The model and controller have been realized in the MATLAB environment. Simulation results indicated that the proposed controller exhibits satisfying control effect.
文摘This paper is concerned with two popular and powerful methods in electrical drive applications:fieldoriented control(FOC)and space vector modulation(SVM).The proposed FOC-SVM method is incorporated with a predictive current control(PCC)-based technique.The suggested method estimates the desirable electrical torque to track mechanical torque at a fixed speed operation of permanent magnet synchronous motor(PMSM).The estimated torque is used to calculate the reference current based on FOC.In order to improve the performance of the traditional SVM,a PCC method is established as a switching pattern modifier.Therefore,PCC-based SVM is employed to further minimize the torque ripples and transient response.The performance of the controller is evaluated in terms of torque and current ripple and transient response to step variations of the torque command.The proposed method has been verified with MATLAB-Simulink model.Simulation results confirm the ability of this technique in minimizing the torque and speed ripples and fixing switching frequency,simultaneously.However,it is sensitive to parameter changes.
文摘This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generator (SEIG). The aim of the developed control method is to automatically tune and optimize the scaling factors and the membership functions of the Fuzzy Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated voltage source PWM converters with a carrier-based Sinusoidal PWM modulation for both Generator- and Grid-side converters have been connected back to back between the generator terminals and utility grid via common DC link. The indirect vector control scheme is implemented to maintain balance between generated power and power supplied to the grid and maintain the terminal voltage of the generator and the DC bus voltage constant for variable rotor speed and load. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and also machine parameters mismatches. The proposed control scheme has improved the voltage regulation and the transient performance of the wave energy scheme over a wide range of operating conditions.
文摘三电机卷绕系统是一个强耦合非线性时变系统,存在卷轴半径、转动惯量以及摩擦系数等时变参数,导致张力协同控制精度较低.为了提高卷绕系统模型准确度,实时优化张力协同控制系统的动态性能,提出一种基于改进鲸鱼算法优化的多核最小二乘支持向量机回归(multi-kernel least squares support vector regression prediction model based on an improved whale algorithm optimization,WOA-M-LSSVR)预测模型和基于纵横交叉优化算法(crisscross optimization algorithm,CSO)优化的模型预测张力协同控制系统.根据最小二乘支持向量机回归原理建立多核LSSVR回归模型,并使用改进的自适应鲸鱼算法进行离线优化,得到系统预测模型;根据建立的预测模型,构建自适应更新的模型预测控制器,引入纵横交叉优化算法实现优化求解,最大程度避免了求解陷入局部最优的情况,提高了张力控制系统的动态性能.通过仿真和实验分析,验证了所设计的张力协同控制系统具有良好的动态性能和鲁棒性.
