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增益控制

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Draw lessons from increment type observation implement with PI condition observation implement research achievement, combine heat to dominate a field complex control system designs bunchy form normally the actual condition of regulating system, offer observation of function of PI of increment style broad sense implement and the concept that its condition feedbacks, the tectonic regulating system that cluster form and observation implement feedback of shirt-sleeve broad sense condition controls a system, learn an analysis through number, give out the sufficient condition of IFO-PIO/BS reachs his corresponding theorem and deductive proof, announce give this to controlled systematic equivalence to be had at IFO-PIO/BS change the function that gain condition feedbacks.

借鉴增量式观测器和PI状态观测器的探究成果,并结合热控领域复杂控制系统通常设计成串级调节系统的实际情况,提出增量式广义PI函数观测器及其状态反馈的概念,构造串级调节系统和观测器相融合的广义状态反馈控制系统,通过数学分析,给出IFO-PIO/BS的充分条件及其相应定理和推论的证实,揭示出该控制系统等价于IFO-PIO/BS具有了变增益状态反馈的功能。

The floating dock system controlled by the closed loop gain shaping with H(subscript ∞) control theory is studied and simulated.

采用H控制中的闭环增益成形控制算法,对浮船坞控制系统进行了理论探讨和仿真研究。

The influence of backlash and friction was compensated based on RBF neural network variable structure compound contr...

结果表明,RBF神经网络变结构控制降低了增益固定变结构控制的抖振现象,控制精度优于PID控制。

In our thesis, contents are organized as following In Chapter 1 we present our topic's internal and overseas research situations, theoretical and practical significance, and introduce the research object and contents, and the main contributions of this dissertation. Chapter 2 reviews the development of the stability results for nonlinear systems and some relevant recent results, which include Lyapunov and LaSalle-Yoshizawa theorems for nonlinear systems, and stochastic edition for stochastic nonlinear systems. Sontag's formula for systems affine in control is presented in the frame of CLF. The concepts of disturbance attenuation and the inverse optimality are also explained in this Chapter. In chapter 3 we present the solvable theorem of inverse optimal gain assignment problem, design the inverse optimal controller and the inverse optimal tracking controller for strict-feedback nonlinear continuous systems with unknown time-varing bounded disturbances and constant unknown parameters using an adaptive backstepping algorithm, which are nonlinear, continuous and are easier to realize. These designs are fully systematic and the algorithm can be directly coded in symbolic software. The results of simulation show the effectiveness of the control algorithms.

论文的结构如下:在第1章中,给出了本文研究课题的研究现状、理论意义和实际应用,并介绍了本文的研究对象、研究内容以及主要贡献;在第2章中,针对确定性非线性系统和随机非线性系统,分别介绍了Lyapunov定理、LaSalle-Yoshizawa定理及其随机版本;对仿射系统,在控制Lyapunov函数框架下,给出了Sontag公式;同时给出了非线性系统扰动抑制和逆最优控制问题的基本概念;在第3章中,针对具有未知时变有界扰动和未知定常参数的一类不确定非线性系统,给出并证明了逆最优增益配置可解定理,使用自适应Backstepping算法和均值定理,系统地设计了自适应逆最优控制器和逆最优跟踪器,这种设计方法可同时获得逆最优控制策略和自适应律,简单明了,仿真结果表明该控制算法的有效性,并给出了性能估计。

The Langford system, which is the same as the Chen and Chua\'s system in being 3D system but different from them in amplitude control application, can be controlled in amplitude of limit cycle directly and effectively and the control gains can be optimized conveniently.

不同于对Chen系统和Chua系统的幅值控制,对于同样是三维的Langford系统,其极限环的幅值控制更加直接而有效,便于实现控制增益的优化设计,而且,对于给定的幅值控制目标,可直接针对原系统进行控制器设计。

The gain of the proposed AGCC can be obtained by solving a series of linear matrix inequalities.

该控制策略通过引入自适应机制降低固定增益控制器所固有的保守性,并且控制器的反馈增益应用线性矩阵不等式方法解得。

The magnitude of sliding mode switching gain is the key reason causing system chattering. Self-recurrent wavelet neural networks is used to estimate sliding mode switching gain on-line, which can reduce chattering caused by sliding mode control effectively.

滑模开关增益的大小是造成系统抖振的关键,采用自回归小波神经网络(Self-recurrent wavelet neural networks, SRWNN)在线估计滑模开关增益的大小可以有效降低滑模控制造成的抖振。

It shows that the control pulse width, the SOA length effect and the nonlinear gain compression effect influence the width of the switching window, and they are the main factors in limiting the switching speed of the CPMZ configuration.

研究表明:控制脉冲宽度、半导体光放大器的长度和非线性增益压缩影响着控制脉冲和信号脉冲反向传播开关窗口的大小,是限制控制脉冲和信号脉冲反向传播高速工作的主要因素。

In order to improve the arithmetic, a king of self - correcting gain K adaptive PID control way is presented by using recursion formula of gain K in adaptive PSD controller.

并推导了为改进其应用上的不足,将自适应PSD控制器中递推计算增益K的方法应用到单神经元的自适应PID控制,构成具有自动调整增益K值的单神经元自适应PID控制器的学习算法。

If control horizon is weighted as usual, it results in constraint control law. Author proposes pseudo weighted control scheme which avoids assumption of inverse stability.

最后,又提出了该模型自适应逆动态组合极点配置控制方案该方案的新颖之处就在于构造非线性增益自适应动态逆,用来补偿非线性增益。

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