The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the pre...This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the predictions of physical designs because of errors in mechanical matching and installation.Therefore,parameter optimization methods such as pointwise scanning,evolutionary algorithms(EAs),and robust conjugate direction search are widely used in beam tuning to compensate for this inconsistency.However,it is difficult for them to deal with a large number of discrete local optima.The A3C algorithm,which has been applied in the automated control field,provides an approach for improving multi-dimensional optimization.The A3C algorithm is introduced and improved for the real-time beam tuning code for accelerators.Experiments in which optimization is achieved by using pointwise scanning,the genetic algorithm(one kind of EAs),and the A3C-algorithm are conducted and compared to optimize the currents of four steering magnets and two solenoids in the low-energy beam transport section(LEBT)of the Xi’an Proton Application Facility.Optimal currents are determined when the highest transmission of a radio frequency quadrupole(RFQ)accelerator downstream of the LEBT is achieved.The optimal work points of the tuned accelerator were obtained with currents of 0 A,0 A,0 A,and 0.1 A,for the four steering magnets,and 107 A and 96 A for the two solenoids.Furthermore,the highest transmission of the RFQ was 91.2%.Meanwhile,the lower time required for the optimization with the A3C algorithm was successfully verified.Optimization with the A3C algorithm consumed 42%and 78%less time than pointwise scanning with random initialization and pre-trained initialization of weights,respectively.展开更多
a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic...a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.展开更多
A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that...A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.展开更多
An aircraft quadrotor is a complex control system that allows for great flexibility in flight.Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available...An aircraft quadrotor is a complex control system that allows for great flexibility in flight.Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available,known,and accurate.The inclusion of payload changes the dynamic characteristics of the aircraft,making it necessary to adapt the control system for this situation.Among the various control methods that have been investigated,proportional-integralderivative(PID)control offers good results and simplicity of application;however,achieving stability and high performance is challenging,with the most critical task being tuning the controller gains.The Ziegler-Nichols(ZN)theory was used to tune the controller gains for pitch and roll attitude command;however,the performance results were not satisfactory.The response of this system was refined,resulting in an improvement in the reference tracking and the rejection of disturbances.This particular refinement was applied to the quadrotor,and via a reverse calculation,the parameters that allow the tuning of PID gains were obtained,based on ZN.The particularization of the ZN theory applied to a quadrotor with and without a load(termed ZNAQ and ZNAQL,respectively)is proposed and results in a significant improvement in the control system response performance(up to 75%),demonstrating that ZNAQ and ZNAQL are valid for tuning the controller PID gains and are more efficient than the original ZN theory approach.展开更多
The correct rate of detection for fabric defect is affected by low contrast of images. Aiming at the problem,frequencytuned salient map is used to detect the fabric defect. Firstly,the images of fabric defect are divi...The correct rate of detection for fabric defect is affected by low contrast of images. Aiming at the problem,frequencytuned salient map is used to detect the fabric defect. Firstly,the images of fabric defect are divided into blocks. Then,the blocks are highlighted by frequency-tuned salient algorithm. Simultaneously,gray-level co-occurrence matrix is used to extract the characteristic value of each rectangular patch. Finally,PNN is used to detect the defect on the fabric image. The performance of proposed algorithm is estimated off-line by two sets of fabric defect images. The theoretical argument is supported by experimental results.展开更多
为解决现有算法选择方法需要复杂流程和专业知识的问题,提出了一种基于大语言模型的强化学习策略。该方法通过参数高效微调对大语言模型进行初始化,为后续的强化学习训练提供高质量的基础。利用指导策略对微调后的模型进行强化学习训练...为解决现有算法选择方法需要复杂流程和专业知识的问题,提出了一种基于大语言模型的强化学习策略。该方法通过参数高效微调对大语言模型进行初始化,为后续的强化学习训练提供高质量的基础。利用指导策略对微调后的模型进行强化学习训练,完成算法选择任务。实验结果表明,在图形类、回归类和控制图类3个场景中,AS-LLM(algorithm selection-large language model)的准确率分别比其它方法的平均准确率高2.23、6.22和5.57个百分点。该方法显著提升了算法选择性能和有效性,且更易于用户操作。展开更多
To reduce the vibration in the suspension, semi active suspension system was employed. And its CARMA model was built. Two adaptive control schemes, the minimum variance self tuning control algorithm and the pole con...To reduce the vibration in the suspension, semi active suspension system was employed. And its CARMA model was built. Two adaptive control schemes, the minimum variance self tuning control algorithm and the pole configuration self tuning control algorithm, were proposed. The former can make the variance of the output minimum while the latter can make dynamic behavior satisfying. The stability of the two schemes was analyzed. Simulations of them show that the acceleration in the vertical direction has been reduced greatly. The purpose of reducing vibration is realized. The two schemes can reduce the vibration in the suspension and have some practicability.展开更多
在五轴联动数控加工中心中,由于液压托架升降系统受到多种因素的共同影响,多因素耦合导致控制系统无法选出关键因素进行补偿操作,控制过程过于复杂,动态响应能力差,提出轴联动数控加工中心液压托架升降伺服控制方法。通过随机森林算法(R...在五轴联动数控加工中心中,由于液压托架升降系统受到多种因素的共同影响,多因素耦合导致控制系统无法选出关键因素进行补偿操作,控制过程过于复杂,动态响应能力差,提出轴联动数控加工中心液压托架升降伺服控制方法。通过随机森林算法(Random Forest,RF)对影响液压托架升降性能的多种因素进行智能识别与约减,从众多因素中筛选出对升降系统性能有显著影响的关键因素,简化了控制因素的输入,减少了多因素的相互耦合作用。采用基于内模控制(Internal Model Control,IMC)与比例-积分-微分(Proportion-Integration-Differentiation,PID)控制相结合的复合控制策略,利用IMC的预测能力和PID的快速响应特性分析控制因素,有效提升了升降系统对动态变化的适应能力和抗干扰能力。为了进一步优化PID控制器的参数,引入蒲公英算法(Dandelion Algorithm,DA)进行全局优化,通过智能搜索算法找到最优的PID参数组合,提高了控制的稳定性和精度。试验结果表明,所提方法有效提高了液压托架升降伺服系统的控制效率、稳定性以及准确度。展开更多
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal ...A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.展开更多
Choosing optimal parameters for support vector regression （SVR） is an important step in SVR. design, which strongly affects the pefformance of SVR. In this paper, based on the analysis of influence of SVR parameters...Choosing optimal parameters for support vector regression （SVR） is an important step in SVR. design, which strongly affects the pefformance of SVR. In this paper, based on the analysis of influence of SVR parameters on generalization error, a new approach with two steps is proposed for selecting SVR parameters, First the kernel function and SVM parameters are optimized roughly through genetic algorithm, then the kernel parameter is finely adjusted by local linear search, This approach has been successfully applied to the prediction model of the sulfur content in hot metal. The experiment results show that the proposed approach can yield better generalization performance of SVR than other methods,展开更多
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
文摘This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the predictions of physical designs because of errors in mechanical matching and installation.Therefore,parameter optimization methods such as pointwise scanning,evolutionary algorithms(EAs),and robust conjugate direction search are widely used in beam tuning to compensate for this inconsistency.However,it is difficult for them to deal with a large number of discrete local optima.The A3C algorithm,which has been applied in the automated control field,provides an approach for improving multi-dimensional optimization.The A3C algorithm is introduced and improved for the real-time beam tuning code for accelerators.Experiments in which optimization is achieved by using pointwise scanning,the genetic algorithm(one kind of EAs),and the A3C-algorithm are conducted and compared to optimize the currents of four steering magnets and two solenoids in the low-energy beam transport section(LEBT)of the Xi’an Proton Application Facility.Optimal currents are determined when the highest transmission of a radio frequency quadrupole(RFQ)accelerator downstream of the LEBT is achieved.The optimal work points of the tuned accelerator were obtained with currents of 0 A,0 A,0 A,and 0.1 A,for the four steering magnets,and 107 A and 96 A for the two solenoids.Furthermore,the highest transmission of the RFQ was 91.2%.Meanwhile,the lower time required for the optimization with the A3C algorithm was successfully verified.Optimization with the A3C algorithm consumed 42%and 78%less time than pointwise scanning with random initialization and pre-trained initialization of weights,respectively.
文摘a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.
文摘A new searching algorithm named the annealing-genetic algorithm(AGA) was proposed by skillfully merging GA with SAA. It draws on merits of both GA and SAA ,and offsets their shortcomings.The difference from GA is that AGA takes objective function as adaptability function directly,so it cuts down some unnecessary time expense because of float-point calculation of function conversion.The difference from SAA is that AGA need not execute a very long Markov chain iteration at each point of temperature, so it speeds up the convergence of solution and makes no assumption on the search space,so it is simple and easy to be implemented.It can be applied to a wide class of problems.The optimizing principle and the implementing steps of AGA were expounded. The example of the parameter optimization of a typical complex electromechanical system named temper mill shows that AGA is effective and superior to the conventional GA and SAA.The control system of temper mill optimized by AGA has the optimal performance in the adjustable ranges of its parameters.
文摘An aircraft quadrotor is a complex control system that allows for great flexibility in flight.Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available,known,and accurate.The inclusion of payload changes the dynamic characteristics of the aircraft,making it necessary to adapt the control system for this situation.Among the various control methods that have been investigated,proportional-integralderivative(PID)control offers good results and simplicity of application;however,achieving stability and high performance is challenging,with the most critical task being tuning the controller gains.The Ziegler-Nichols(ZN)theory was used to tune the controller gains for pitch and roll attitude command;however,the performance results were not satisfactory.The response of this system was refined,resulting in an improvement in the reference tracking and the rejection of disturbances.This particular refinement was applied to the quadrotor,and via a reverse calculation,the parameters that allow the tuning of PID gains were obtained,based on ZN.The particularization of the ZN theory applied to a quadrotor with and without a load(termed ZNAQ and ZNAQL,respectively)is proposed and results in a significant improvement in the control system response performance(up to 75%),demonstrating that ZNAQ and ZNAQL are valid for tuning the controller PID gains and are more efficient than the original ZN theory approach.
文摘The correct rate of detection for fabric defect is affected by low contrast of images. Aiming at the problem,frequencytuned salient map is used to detect the fabric defect. Firstly,the images of fabric defect are divided into blocks. Then,the blocks are highlighted by frequency-tuned salient algorithm. Simultaneously,gray-level co-occurrence matrix is used to extract the characteristic value of each rectangular patch. Finally,PNN is used to detect the defect on the fabric image. The performance of proposed algorithm is estimated off-line by two sets of fabric defect images. The theoretical argument is supported by experimental results.
文摘为解决现有算法选择方法需要复杂流程和专业知识的问题,提出了一种基于大语言模型的强化学习策略。该方法通过参数高效微调对大语言模型进行初始化,为后续的强化学习训练提供高质量的基础。利用指导策略对微调后的模型进行强化学习训练,完成算法选择任务。实验结果表明,在图形类、回归类和控制图类3个场景中,AS-LLM(algorithm selection-large language model)的准确率分别比其它方法的平均准确率高2.23、6.22和5.57个百分点。该方法显著提升了算法选择性能和有效性,且更易于用户操作。
文摘To reduce the vibration in the suspension, semi active suspension system was employed. And its CARMA model was built. Two adaptive control schemes, the minimum variance self tuning control algorithm and the pole configuration self tuning control algorithm, were proposed. The former can make the variance of the output minimum while the latter can make dynamic behavior satisfying. The stability of the two schemes was analyzed. Simulations of them show that the acceleration in the vertical direction has been reduced greatly. The purpose of reducing vibration is realized. The two schemes can reduce the vibration in the suspension and have some practicability.
文摘在五轴联动数控加工中心中,由于液压托架升降系统受到多种因素的共同影响,多因素耦合导致控制系统无法选出关键因素进行补偿操作,控制过程过于复杂,动态响应能力差,提出轴联动数控加工中心液压托架升降伺服控制方法。通过随机森林算法(Random Forest,RF)对影响液压托架升降性能的多种因素进行智能识别与约减,从众多因素中筛选出对升降系统性能有显著影响的关键因素,简化了控制因素的输入,减少了多因素的相互耦合作用。采用基于内模控制(Internal Model Control,IMC)与比例-积分-微分(Proportion-Integration-Differentiation,PID)控制相结合的复合控制策略,利用IMC的预测能力和PID的快速响应特性分析控制因素,有效提升了升降系统对动态变化的适应能力和抗干扰能力。为了进一步优化PID控制器的参数,引入蒲公英算法(Dandelion Algorithm,DA)进行全局优化,通过智能搜索算法找到最优的PID参数组合,提高了控制的稳定性和精度。试验结果表明,所提方法有效提高了液压托架升降伺服系统的控制效率、稳定性以及准确度。
基金This work was supported by the National Natural Science Foundation of China (No. 50275150)the Foundation of Robotics Laboratory, Chinese Academy of Sciences( No. RL200002).
文摘A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.
文摘Choosing optimal parameters for support vector regression （SVR） is an important step in SVR. design, which strongly affects the pefformance of SVR. In this paper, based on the analysis of influence of SVR parameters on generalization error, a new approach with two steps is proposed for selecting SVR parameters, First the kernel function and SVM parameters are optimized roughly through genetic algorithm, then the kernel parameter is finely adjusted by local linear search, This approach has been successfully applied to the prediction model of the sulfur content in hot metal. The experiment results show that the proposed approach can yield better generalization performance of SVR than other methods,
