针对采用矢量控制方法的内置式永磁同步电机(IPMSM)存在解耦复杂、附加优化目标难以融入系统控制等问题,提出了一种基于最大转矩电流比(MTPA)的IPMSM转矩预测控制方法。在推导MTPA控制原理的基础上,分析了转矩预测的控制机理及性能指标...针对采用矢量控制方法的内置式永磁同步电机(IPMSM)存在解耦复杂、附加优化目标难以融入系统控制等问题,提出了一种基于最大转矩电流比(MTPA)的IPMSM转矩预测控制方法。在推导MTPA控制原理的基础上,分析了转矩预测的控制机理及性能指标函数。22 k W试验样机的仿真与试验结果表明,系统稳态及全局加减负载条件下调速性能良好、转矩动态响应迅速。该方法在重载条件下定子电流利用率显著提高,满足电动车辆驱动控制系统的性能和效率指标要求。展开更多
Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a s...Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.展开更多
A policy iteration algorithm of adaptive dynamic programming(ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking proble...A policy iteration algorithm of adaptive dynamic programming(ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.展开更多
This paper presents a method for solving the attitude control problem of high altitude airship (HAA) with aerodynamic fin and vectored thruster control. The algorithm is based on the synthetic optimization of dynamic ...This paper presents a method for solving the attitude control problem of high altitude airship (HAA) with aerodynamic fin and vectored thruster control. The algorithm is based on the synthetic optimization of dynamic performance and energy consumption of airship. Firstly, according to the system overall configuration, the dynamic model of HAA was established and the HAA linearized model of longitudinal plane motion was obtained. Secondly, using the classic PID control theory, the HAA attitude control system was designed. Thirdly, through analyzing the dynamic performance of airship with fin or vectored thruster control, the synthetic performance index function with different weighting functions was determined. By means of optimizing the obtained performance index function, the attitude control of high altitude airship with good dynamic performance and low energy consumption was achieved. Finally, attitude control allocation strategy was designed for the airship station keeping at an altitude of 22 km. The simulation experiment proved the validity of the proposed algorithm.展开更多
文摘针对采用矢量控制方法的内置式永磁同步电机(IPMSM)存在解耦复杂、附加优化目标难以融入系统控制等问题,提出了一种基于最大转矩电流比(MTPA)的IPMSM转矩预测控制方法。在推导MTPA控制原理的基础上,分析了转矩预测的控制机理及性能指标函数。22 k W试验样机的仿真与试验结果表明,系统稳态及全局加减负载条件下调速性能良好、转矩动态响应迅速。该方法在重载条件下定子电流利用率显著提高,满足电动车辆驱动控制系统的性能和效率指标要求。
基金Projects(90820302,60805027)supported by the National Natural Science Foundation of ChinaProject(200805330005)supported by the Research Fund for the Doctoral Program of Higher Education,ChinaProject(2009FJ4030)supported by Academician Foundation of Hunan Province,China
文摘Multi-target tracking(MTT) is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member(CM) node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.
基金supported by the National Natural Science Foundation of China(Grant Nos.61034002,61233001,61273140,61304086,and 61374105)the Beijing Natural Science Foundation,China(Grant No.4132078)
文摘A policy iteration algorithm of adaptive dynamic programming(ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.
文摘This paper presents a method for solving the attitude control problem of high altitude airship (HAA) with aerodynamic fin and vectored thruster control. The algorithm is based on the synthetic optimization of dynamic performance and energy consumption of airship. Firstly, according to the system overall configuration, the dynamic model of HAA was established and the HAA linearized model of longitudinal plane motion was obtained. Secondly, using the classic PID control theory, the HAA attitude control system was designed. Thirdly, through analyzing the dynamic performance of airship with fin or vectored thruster control, the synthetic performance index function with different weighting functions was determined. By means of optimizing the obtained performance index function, the attitude control of high altitude airship with good dynamic performance and low energy consumption was achieved. Finally, attitude control allocation strategy was designed for the airship station keeping at an altitude of 22 km. The simulation experiment proved the validity of the proposed algorithm.
