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prediction horizon
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  预测视野
     The result shows that the prediction horizon of the nonlinear method is farther than that of the linear one, and moreover, the overall performance within the prediction horizon excels that of the linear prediction, though the computation of the former is somewhat heavier than that of the linear method.
     结果表明 ,尽管非线性的局域线性预测法存在计算开销大的问题 ,但其预测视野要远大于线性预测法 ,总体预测性能明显优于线性预测法 .
短句来源
  预测时域
     In the algorithm,Laguerre functions are used to describe the control signals from the dynamic linear section of Wiener model,and the optimization solutions of the future control input sequences in predictive control are converted into the optimization of a set of immemorial Laguerre coefficients within prediction horizon in order to reduce the computation burden in optimization.
     该算法利用Laguerre函数描述Wiener模型动态线性部分的控制信号,将预测控制中在预测时域内优化求解未来控制输入序列转化为优化求解一组无记忆的Laguerre系数,以减少优化所需的计算量.
短句来源
     Simple Criteria for Choosing the Prediction Horizon
     预测时域选择的简易判据
短句来源
     Laguerre functions are used to describe control input of linear section of Wiener model, optimization solutions of the future control input sequences are converted into optimization of a set of immemorial Laguerre coefficients in prediction horizon.
     该方法将Wiener模型线性部分的控制增量信号描述成Laguerre级数展开式,将预测控制中在预测时域内优化求解未来控制输入序列转化为优化求解一组无记忆的Laguerre系数,以减少优化所需的计算量;
短句来源
     It selects ESN with the mechanism of the "reservoir" as predict model to set up a direct predict method which directly relates the prediction origin and prediction horizon.
     通过选取具有储备池机制的回声状态网络ESN作为网络预测模型,建立一种直接预测方法,直接构建预测原点和预测时域之间的定量关系。
短句来源
     ome simple criteria for choosing the prediction horizon in Extended Horizon Predictive Control (EHPC) are presented, so that the closed loop system is asymptotically stable.
     提出了预测控制中选择预测时域的判据,用以保证闭环系统的渐近稳定性。
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  “prediction horizon”译为未确定词的双语例句
     It is proved that globally asymptotical stability and convergence of the resulting closed-loop system are guaranteed by the range of the prediction horizon.
     从理论上证明了它可保证闭环系统的全局渐近稳定和收敛,并定量给出了预测水平的选择范围。
短句来源
     In this paper,the fast recursive algorithms of Generalized Predictive Control (GPC) are proposed by transforming the performance function with a backward recursion approach. The algorithms are recursively performed with O(n. N) computations for an n-th order plant and N-step prediction horizon,and arefaster than the traditional GPC algotithms. The simulation results show their effectiveness.
     本文利用反向递推方法对广义预测控制(GPC)的准则函数进行变换,得出一种违推的快速GPC算法.该算法对预测长度为N的阶系统的计算量仅为O(N·n),优于传统的求解Dio-Phantine方程或矩阵求道的算法.仿真结果表明了算法的有效性.
短句来源
     Under model plant mismatch the robustly asymptotic stability and global convergence of the resulting closed loop system are guaranteed by selecting proper prediction horizon.
     同时给出了在模型失配情况下保证闭环系统全局渐近稳定的预报长度范围和模型失配上限值 .
短句来源
     A non linear wavelet neural network model based domain predictive control scheme was introduced for open loop stable systems subjected to input constraints. Its closed loop stability was guaranteed by an appropriate choice of a finite prediction horizon.
     对开环稳定过程 ,引入一个具有输入约束的基于小波神经网络模型的区域预测控制方案 ,它的闭环稳定性能够通过适当选择它的预测水平来保证。
短句来源
     For a multi-rate sample system with different output sampling and input updating described by state-space model,a multi-rate single predictive control algorithm based on single predictive method is proposed,and the closed-loop system properties are analyzed. The sufficient and necessary conditions that make the multi-rate predictive control system stable are given in this paper,and we can conclude that the stability of the closed-loop system can be realized by adjusting the length of the prediction horizon.
     针对一类输入输出采用不同频率的多速率采样系统进行研究,提出了基于状态空间模型下的单值广义预测控制(MSGPC)算法,分析了系统的闭环稳定性问题,并给出了多速率预测控制系统稳定的充要条件,得到了闭环系统的稳定性可以通过适当调节预报时域长度来实现的结论。
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  prediction horizon
From the comparison, it was found that the prediction method based on the ANN gives an acceptable accuracy for the limited prediction horizon.
      
From the comparison it can be seen that the prediction scheme based on the parameter estimation method gives a reasonable accuracy with limited prediction horizon.
      
A theoretical analysis reveals that attention to the choice of the prediction horizon Δ gives a distinct improvement in the spectral estimate and in the resolution of the signals.
      
The obtained model was used to predict cycles 24 and 25, although the forecast of the latter is seen as a crude approximation, given the long prediction horizon required.
      
This model is a limited area model (mesoscale beta) and the capability to extend the prediction horizon is limited unless proper boundary conditions are provided during long simulations.
      
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The Principle of Model Predictive Heuristic Control (MPHC) technique arediscussed by Richalet [1]. Emara-Shabaik applied MPHC to Automatic rende-zvous of spacecraft [2]. This paper differs from Ref.[2] in control strategy. Our approach is basedon a new real time algorithm for the linear least square solution of MIMO(Multi-input/multi-output) system. This paper differs from Ref. [2] in the design of automatic rendezvoussystem in the following points: 1. The "predictive" feature was practically non-existent in...

The Principle of Model Predictive Heuristic Control (MPHC) technique arediscussed by Richalet [1]. Emara-Shabaik applied MPHC to Automatic rende-zvous of spacecraft [2]. This paper differs from Ref.[2] in control strategy. Our approach is basedon a new real time algorithm for the linear least square solution of MIMO(Multi-input/multi-output) system. This paper differs from Ref. [2] in the design of automatic rendezvoussystem in the following points: 1. The "predictive" feature was practically non-existent in Ref. [2]. In thispaper's design the predictive feature is obviously present. 2. In the design of closed-loop system, this paper is believed to offer twomore advantages than Ref. [2]. (i) It decreases the amplitude of maximum engine thrust. (ii) It increases the flexibility in designing prediction horizon L, smoothingpoints NSM, control switching time TC, and weighting matrix Q. While in Ref.[2] only one parameter t_P (model prediction horizon) can be selected. The numerical simulation results show that in this paper's design the systemperformance is improved, total fuel consumption is decreased and robustnessto external disturbances is satisfactory.

本文讨论了模型预估探测控制(MPHC)的基本原理,推导了线性多变量系统的最优控制算法,对宇宙飞船自动交会控制系统进行了设计。从数字仿真结果表明,该系统具有较好的跟踪性能和抗干扰能力,实现起来也比较简单。

The successive one-step ahead predictions are used for the realization o: multi-step ahead predictions for bilinear stochastic system ( BLSS ) , i. e. the multi-step ahead predictions may simply be obtained via the system model recursions Furthermore, under some assumptions for the simplification of analysis, a Generalized Predictive Caontrol ( GPC ) algorithm for BLSS can be obtained according to the cos function of generalized minimum variance. Numerical simulations have shown that the algorithm proposed is...

The successive one-step ahead predictions are used for the realization o: multi-step ahead predictions for bilinear stochastic system ( BLSS ) , i. e. the multi-step ahead predictions may simply be obtained via the system model recursions Furthermore, under some assumptions for the simplification of analysis, a Generalized Predictive Caontrol ( GPC ) algorithm for BLSS can be obtained according to the cos function of generalized minimum variance. Numerical simulations have shown that the algorithm proposed is feasible, requires less on-line calculation, and possesses high steady state control precision. By adjusting the prediction horizon and properly setting the initial values of parameter estimation, fast starting can be gained withou overshoot. The robustness against stepwise disturbance and time - delay variation is satisfactory.

以模型递推法实现双线性随机系统的多步预报,即重复利用受控对象模型自身包含的一步递推预报关系,依次得出对象输出的多步预报值,并证明了在一定条件下此预报值具有近似最小方差性。进而,利用适当的简化假设,按多步广义最小方差控制性能指标导出了双线性随机系统的广义预报控制算法。数字仿真证明,此控制算法在线计算量少,稳态精度高,通过适当地选取参数估计初值和调整预报步长,可以作到启动平稳、迅捷、几乎无超调,且抗阶跃扰动性能强,对变时延有良好的鲁棒性。

This article presents a dynamic prediction system for an interurban mo-torway network.The system forcasts traffic conditions on the network in real-time,and provides information to a motorway traffic control centre. The models re-ceive traffic data such as traffic flow, average speed and detector occupancy in real-time from a motorway monitoring system,Additionally,a databank of historic traf-fic information will be used. The system contains several submodels:a statistical state space model for fil-tering noisy...

This article presents a dynamic prediction system for an interurban mo-torway network.The system forcasts traffic conditions on the network in real-time,and provides information to a motorway traffic control centre. The models re-ceive traffic data such as traffic flow, average speed and detector occupancy in real-time from a motorway monitoring system,Additionally,a databank of historic traf-fic information will be used. The system contains several submodels:a statistical state space model for fil-tering noisy data,and for very short prediction(prediction horizon:5~15min);a dynamic traffic assignment model for short term prediction(15~60min );a real-time O/D matrix prediction model to provide the input flows to the statistical and assignment models. Predictions from the two models are merged where their re-spective time horizons overlap.

本文介绍一城市间高速公路网的动态交通预测模式系统。该系统实时预测网络的交通状况并把信息及时传送给交通控制中心。模式实时接受来自交通监测中心的交通流、平均速度及传感器占有率等交通数据。此外,模式也使用已有交通信息的数据库。模式系统主要由三个子系统组成:统计空间模式、动态加载模式和实时预测模式。子系统一用于过滤不稳定的交通数据并作出极短时间内的交通预测(5~15分钟);子系统二用于短时间内的预测(15~60分钟);子系统三则给前两个子系统输入流量。主系统综合各子系统的结果并作出交通预测。

 
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