Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy...Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.展开更多
In the strip rolling process, shape control system possesses the characteristics of nonlinearity, strong coupling, time delay and time variation. Based on self adapting Elman dynamic recursion network prediction model...In the strip rolling process, shape control system possesses the characteristics of nonlinearity, strong coupling, time delay and time variation. Based on self adapting Elman dynamic recursion network prediction model, the fuzzy control method was used to control the shape on four-high cold mill. The simulation results showed that the system can be applied to real time on line control of the shape.展开更多
The attitude adjustment of rope system faces the challenging due to the difficulty in obtaining accurate three-dimensional(3D)mathematical model and solving by traditional methods.A set of adjustment systems is design...The attitude adjustment of rope system faces the challenging due to the difficulty in obtaining accurate three-dimensional(3D)mathematical model and solving by traditional methods.A set of adjustment systems is designed and used to investigate the automatic control for level or preset attitude adjustment of unknown weights and eccentric loads.The system principle and characteristics are analyzed.The 3D model is decomposed into two two-dimensional(2D)subsystems,and an adaptive fuzzy controller based on BP neural network and least squares(LSE)is designed.The simulation experiment uses MATLAB to train the level-adjustment data for testing algorithm,and a small load is used to verify the effectiveness of the system.The experimental results show that precise attitude adjustment can be achieved within the system load range,and the response speed is fast.This adjustment method provides a fast and effective method for precise adjustment of the load attitude.展开更多
With the continuous acceleration of the urbanization process, the development of underground space around the rapid development, rail transit tunnel construction is increasingly perfect. In recent years, the construct...With the continuous acceleration of the urbanization process, the development of underground space around the rapid development, rail transit tunnel construction is increasingly perfect. In recent years, the construction of long and ultra-long distance tunnels is becoming more and more common, and the accuracy requirements are constantly improving. As one of the important difficulties affecting the penetration accuracy, the improvement of the tunnel underground plane control network accuracy is the key issue discussed in this paper. By introducing three methods to improve the accuracy and applying new technology to the long distance tunnel construction survey, combined with the project construction example, it is analyzed that the above three methods can improve the accuracy of the underground plane control network of long distance tunnel, meet the requirement of through-through control, and ensure the quality of the project.展开更多
为避免光伏并网后发生电压越限情况,保证电压运行稳定,提出一种基于光伏逆变器功率控制的电网无功电压调节方法。该方法分析光伏并网对于电压的影响,以此为依据,采用线性计算方法通过3个控制阶段,控制光伏逆变器的功率,获取逆变器有功...为避免光伏并网后发生电压越限情况,保证电压运行稳定,提出一种基于光伏逆变器功率控制的电网无功电压调节方法。该方法分析光伏并网对于电压的影响,以此为依据,采用线性计算方法通过3个控制阶段,控制光伏逆变器的功率,获取逆变器有功和无功两种功率的控制调整量;依据该控制量确定电网无功电压调节的目标函数和约束条件,并利用改进的混沌遗传算法,求解目标函数,输出无功电压调节结果。测试结果表明,该方法具有可行性,可完成本地电压控制;可有效完成逆变器功率控制,通过功率控制调整量,完成电压控制;可使电压波动率均低于1.25%,有效避免节点发生电压越限情况;并可显著降低配电网中各个节点的网损结果,使其均在5.9 k W/h以下。展开更多
文摘Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.
基金ItemSponsored by Provincial Natural Science Foundation of Hebei Province of China (E2004000206)
文摘In the strip rolling process, shape control system possesses the characteristics of nonlinearity, strong coupling, time delay and time variation. Based on self adapting Elman dynamic recursion network prediction model, the fuzzy control method was used to control the shape on four-high cold mill. The simulation results showed that the system can be applied to real time on line control of the shape.
基金National Natural Science Foundation of China(No.61605177)
文摘The attitude adjustment of rope system faces the challenging due to the difficulty in obtaining accurate three-dimensional(3D)mathematical model and solving by traditional methods.A set of adjustment systems is designed and used to investigate the automatic control for level or preset attitude adjustment of unknown weights and eccentric loads.The system principle and characteristics are analyzed.The 3D model is decomposed into two two-dimensional(2D)subsystems,and an adaptive fuzzy controller based on BP neural network and least squares(LSE)is designed.The simulation experiment uses MATLAB to train the level-adjustment data for testing algorithm,and a small load is used to verify the effectiveness of the system.The experimental results show that precise attitude adjustment can be achieved within the system load range,and the response speed is fast.This adjustment method provides a fast and effective method for precise adjustment of the load attitude.
文摘With the continuous acceleration of the urbanization process, the development of underground space around the rapid development, rail transit tunnel construction is increasingly perfect. In recent years, the construction of long and ultra-long distance tunnels is becoming more and more common, and the accuracy requirements are constantly improving. As one of the important difficulties affecting the penetration accuracy, the improvement of the tunnel underground plane control network accuracy is the key issue discussed in this paper. By introducing three methods to improve the accuracy and applying new technology to the long distance tunnel construction survey, combined with the project construction example, it is analyzed that the above three methods can improve the accuracy of the underground plane control network of long distance tunnel, meet the requirement of through-through control, and ensure the quality of the project.
文摘为避免光伏并网后发生电压越限情况,保证电压运行稳定,提出一种基于光伏逆变器功率控制的电网无功电压调节方法。该方法分析光伏并网对于电压的影响,以此为依据,采用线性计算方法通过3个控制阶段,控制光伏逆变器的功率,获取逆变器有功和无功两种功率的控制调整量;依据该控制量确定电网无功电压调节的目标函数和约束条件,并利用改进的混沌遗传算法,求解目标函数,输出无功电压调节结果。测试结果表明,该方法具有可行性,可完成本地电压控制;可有效完成逆变器功率控制,通过功率控制调整量,完成电压控制;可使电压波动率均低于1.25%,有效避免节点发生电压越限情况;并可显著降低配电网中各个节点的网损结果,使其均在5.9 k W/h以下。
