In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a...In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.展开更多
To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power syst...To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power system are given for the precision requirement,and a control strategy for dual relative control parameters in the dual loop PID is put forward,a load and throttle rotation-speed response model for variable pump and gasoline engine is provided according to a physical process,a simplified neural network structure PID is introduced,and formed mixed neural network PID(MNN PID)to control rotation speed of engine and pressure of variable pump,calculation using the back propagation(BP)algorithm and a self-adapted learning step is made,including a mathematic principle and a calculation flow scheme,the BP algorithm of neural network PID is trained and the control effect of system is simulated in Matlab environment,real control effects of engine rotation speed and variable pump pressure are verified in the experimental bench.Results show that algorithm effect of MNN PID is stable and MNN PID can meet the adjusting requirement of control parameters.展开更多
为解决气动调节阀控制过程中出现的超调大、精度低等问题,本文采用BP神经网络整定出较优的PID(Proportional Integral Derivative)控制参数,对Smith预估控制器以及模糊控制器进行设计,实现了基于BP神经网络的Smith-Fuzzy-PID控制方法。...为解决气动调节阀控制过程中出现的超调大、精度低等问题,本文采用BP神经网络整定出较优的PID(Proportional Integral Derivative)控制参数,对Smith预估控制器以及模糊控制器进行设计,实现了基于BP神经网络的Smith-Fuzzy-PID控制方法。搭建了实验平台,通过阶跃响应实验来对控制方法进行验证,验证结果表明,提出的方法调节过程无超调,调节时间仅为1.9 s,定位精度在±0.5%以内,有效提高了系统的稳定性,实现了气动调节阀的快速精准定位。展开更多
在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算...在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算法的变频器节能控制系统设计。构建以微处理器为核心的变频器节能控制结构,将神经网络与PID控制器相结合,构造自适应PID控制器。结合变频器节能控制结构的能耗计算与反馈,通过自适应调节权值系数完成变频系数调整,降低各频段能耗,实现变频器节能控制研究。实验结果显示,该系统节能效果显著,能耗最高仅为20 J,且相较于对比文献,该系统运行稳定,运行时间短,为变频器节能控制运行提供了保障。展开更多
文摘In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.
基金Supported by the National Natural Science Foundation of China(51305457)。
文摘To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power system are given for the precision requirement,and a control strategy for dual relative control parameters in the dual loop PID is put forward,a load and throttle rotation-speed response model for variable pump and gasoline engine is provided according to a physical process,a simplified neural network structure PID is introduced,and formed mixed neural network PID(MNN PID)to control rotation speed of engine and pressure of variable pump,calculation using the back propagation(BP)algorithm and a self-adapted learning step is made,including a mathematic principle and a calculation flow scheme,the BP algorithm of neural network PID is trained and the control effect of system is simulated in Matlab environment,real control effects of engine rotation speed and variable pump pressure are verified in the experimental bench.Results show that algorithm effect of MNN PID is stable and MNN PID can meet the adjusting requirement of control parameters.
文摘为解决气动调节阀控制过程中出现的超调大、精度低等问题,本文采用BP神经网络整定出较优的PID(Proportional Integral Derivative)控制参数,对Smith预估控制器以及模糊控制器进行设计,实现了基于BP神经网络的Smith-Fuzzy-PID控制方法。搭建了实验平台,通过阶跃响应实验来对控制方法进行验证,验证结果表明,提出的方法调节过程无超调,调节时间仅为1.9 s,定位精度在±0.5%以内,有效提高了系统的稳定性,实现了气动调节阀的快速精准定位。
文摘在当前的电气应用中,变频器控制系统应用广泛,但面临的挑战也愈发明显。特别是在能耗管理方面,由于其缺乏智能调控频段能耗的能力,系统整体能耗偏高。为此,文章提出基于自适应比例-积分-微分(Proportional Integral Derivative,PID)算法的变频器节能控制系统设计。构建以微处理器为核心的变频器节能控制结构,将神经网络与PID控制器相结合,构造自适应PID控制器。结合变频器节能控制结构的能耗计算与反馈,通过自适应调节权值系数完成变频系数调整,降低各频段能耗,实现变频器节能控制研究。实验结果显示,该系统节能效果显著,能耗最高仅为20 J,且相较于对比文献,该系统运行稳定,运行时间短,为变频器节能控制运行提供了保障。
