control input中文是什么意思

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中文翻译
造句

操纵输入信号
控制输入

control n. 1.支配，管理，管制，统制，控制；监督。 2.抑制 ...
input n. 1.【电学】【自动化】输入；输入端。 2.输入电路 ...
input control 输入控制
control wheel input 驾驶盘输入信号
dic digital input control 数字输入控制
input control register 输入控制寄存器
input control shift register 输入控制移位寄存器
input control system 输入控制系统
input control unit 输入控制器
input control valve 输入调节阀
input enable control 输入启动控制
input file control block 输入文件控制块
input format control 输入格式控制
input output control 输入输出控制
input power control 输入电源控制; 输入功率控制
input stream control 输入流控制
input-output control 输入/输出控制
input-output control center 输入
input-output control command 输入
input-output control program 输入输出控制程序
introduce control input 偏舵
manual-control input 人工控制信号输入
peripheral input output control 外围控制输入输出
post-stall control input 失速后操纵舵面
pulse control input 脉冲式舵面偏转

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例句与用法

And the most important thing is to find the relationship between the control functions or plant states and their control inputs , so as to make every object as satisfied as possible , or reach to a compromise whole maximum
而且最重要的是要寻找一个控制函数或者对象状态与其控制输入之间的函数关系，从而使得每一个控制目标都可以达到尽可能高的满意程度，或者达到某些折衷意义上的最优值。
Iterative learning control is an important branch of intelligent control . the basic method of traditional ilc is to achieve control input based on the previous input and the pid - revised error of previous output . after some iteration , perfect tracking can be achieved over a fixed time interval
迭代学习控制理论是智能控制的一个重要分支，传统迭代学习的基本方法是，基于上次迭代时的输入信息和输出误差的pid校正项，获得本次迭代的控制输入，经过若干次迭代，以期达到在给定的时间区间上实现被控对象以较高精度跟踪一给定目标轨线。
The new scheme employs a recursive algorithm to design controllers for every subsystem , respectively , and takes predesigned control inputs as disturbances . by using lyapunov method , the state of the closed - loop control system is proved to be bounded , with tracking error converging to zero
该方案通过逐层递推的方法，分别针对每一个子系统单独设计控制器，将本层之前已设计好的多项控制输入作为等价干扰，利用李亚普诺夫方法，先证明闭环系统的状态有界，再证明跟踪误差渐近收敛到零。
Abstract : iterative learning control is an effective approach to the control of processes that are repetitive in nature . in this paper , an open - closed - loop pi - type iterative learning control scheme for the precise tracking control of a class of discrete nonlinear time - varying systems over a finite time interval is presented . the scheme updates control input with tracking errors of both current and last iterations simultaneously . sufficient and necessary conditions which guarantee the convergence of the scheme are given and then proved with inductive method . finally , the conditions are verified with simulation results
文摘:对于具有重复运动性质的对象，迭代学习控制是一种有效的控制方法.针对一类离散非线性时变系统在有限时域上的精确轨迹跟踪问题，提出了一种开闭环pi型迭代学习控制律.这种迭代律同时利用系统当前的跟踪误差和前次迭代控制的跟踪误差修正控制作用.给出了所提出的学习控制律收敛的充分必要条件，并采用归纳法进行了证明.最后用仿真结果对收敛条件进行了验证
So it can be used as one part of the industrial process control or a valuable associated software for analyzing and simulating control systems . iterative learning control based on the study of robotic control adjusts control input repetitively with simple learning control algorithms , using input and output data of the previous operation over a fixed time interval , until perfect tracking is achieved
在机器人背景下发展起来的迭代学习控制对解决具有某种重复运动（运行）轨迹跟踪问题具有独特的能力，本文研究的目的是利用迭代学习控制理论为一般控制系统的设计性能优良的控制器，以期扩大迭代学习控制的应用领域。
The main idea under controller design is damping model nonlmearities with control input to force the system dynamic into a linear sliding surface and utilizing dynamic filters to ensure the boundedness of states , inputs and outputs . the mismatched model uncertainties are suppressed with extra items in control input
Dsc控制器通过对消系统非线性项，将系统动态驱至线性滑模态；引入动态滤波器，确保系统的状态及输入输出有界，同时避免了对非线性模型多次求导带来的复杂性；在虚拟控制输入中利用附加项来克服不满足匹配条件的不确定性。
Using the sampled controlling parameters of the aircraft under pure proportional navigation ( ppn ) , the thesis designs the corresponding discrete input signal of the guidance controller under the inside demand of the pursuing control , and trains a module of rbf off - line . then , the module is inserted into the control system of the aircraft and acted as its control input in order that the optimal function of the aircraft under ppn can be realized
在分析比例导引律导引载机追踪/截获目标的状态轨迹的基础上,阐述径向基神经网络的非线性功能特点,根据载机追捕目标的内在要求,设计并训练径向神经网络模块,嵌入载机导引器的控制回路,实现优化载机导引控制。
For these reasons , we can apply the theory of the model reference self - adaptive control syetem design based on the theorem of balance point stabilization in the force system of asymmetric cylinder controlled by symmetric valve . the main idea of model reference self - adaptive controller is to make the self - adaptive control error incline to zero as time passed . the task to design adaptive controller is to find the control input that can make the output of the controlled system to follow that of the reference model
因此将基于平衡点稳定定理的模型参考自适应控制系统设计理论应用于阀控非对称缸力系统中,其基本原理是使自适应控制误差随时间的推移而趋向于零,自适应控制器设计的目的是寻找使被控系统的输出渐近一致的跟随参考模型的输出的控制输入,以此来改善被控系统的性能。
Abstract : an integrating model combining the artificial neura l network with the linear arx model and its identification method is proposed . based on that model , a multivariable nonlinear predictive control algorithm is persented . the algorithm employs the result of the linear predictive control , obtains explicit nonlinear optimal controlling inputs and doesn " t need on - line numerical optimizing which is necessary in general nonlinear model ( including ann model ) predictive control . that greatly decreases on - line computing consumption , strengthens the reliability of the algorithm and the stability of the system . the simulation results in cstr are shown
文摘:提出了一种由人工神经网络与线性arx模型相结合的集成模型，给出了其辨识训练方法.以此模型为基础，提出了一种多变量非线性预测控制算法.它利用线性预测控制的成果，得到一解析式的非线性优化控制输入，避免了通常非线性模型(包括普通人工神经网络模型)预测控制所需的在线数值寻优计算，节约了在线计算时间，提高了算法的可靠性和稳定性.进一步给出了在cstr反应器上的仿真实验结果
Iterative learning control ( ilc ) is a technique for improving the transient response performance of systems or processes that operate repetitively over a fixed time interval . it refines the next control input using the information such as current control input and error signals after each trial until the specified desired trajectory is followed to a high precision
迭代学习控制针对具有重复运行性质的被控对象，利用对象以前运行的信息，通过迭代的方式修正控制信号，实现在有限时间区间上的完全跟踪任务。