并用对偶方法刻画了最优控制律的特征。
By duality approach, we characterize the optimal control law.
利用动态逆方法设计了快子系统控制律。
The slow subsystem control law is designed by Lyapunov method.
推导了自适应控制律与相应的约束条件。
The adaptive control laws and constrain conditions are derived out.
取补偿项序列的有限次迭代值，获得次优控制律。
By taking a finite - time iteration of the compensation sequence, a suboptimal control law is obtained.
分析的结果说明了无模型控制律具有良好的性能。
The results of analysis show that the properties of control law without model are satisfactory.
通过逐步迭代，最终给出了控制律的参数表达式。
Finally the parameter expression of system's controller is obtained by gradually iteration.
在线性情形，它与最小方差参数自适应控制律一致。
In the linear case, it is the same as the minimum variance parameter adaptive control.
该控制律中部分状态允许适度小的饱和限制与时滞。
Partial state variables in the controller admit moderate small saturation restriction and time delay.
然后利用灵敏度法推导出了该系统的最优跟踪控制律。
Then, the optimal tracking control law of this system was deduced through the sensitivity approach.
则离散时滞最优控制律可以针对增广的系统进行设计。
Discrete optimal control algorithm can be designed based on the augmented state system.
在此基础上，再将最优控制律转化为最优重复控制律。
Based on this, the optimal control law is transformed into the optimal repetitive control law.
型迭代学习控制律是迭代学习控制的一种主要学习律。
D-type iterative learning control (ILC) law is one of the main laws of ILC.
传统的D型迭代学习控制律依赖于被控系统的相对度。
The classical D-type ILC law depends on the relative degree of the controlled system.
两种控制律不需要知道系统参数，对模型误差具有鲁棒性。
Both control laws do not require the knowledge of the system parameters and are robust to modeling errors.
通过选择合适的控制算法和控制律，使控制系统达到优化。
The control system reaches the optimum by choosing the right control algorithm and control strategy.
通过综合分析减损控制律，可对控制输入序列进行优化选择。
To select a suitable control input sequence, the DMC law is analyzed and synthesized.
可以在实验室完成对模型系统的控制实验，进行控制律的研究。
We can complete its control experiments in the laboratory, and do research on control rules.
基于反馈对消技术的应用，通过极点配置获得状态反馈控制律。
By feedback cancellation technique, a state feedback control law is obtained by pole placement.
并证明了该最优输出反馈控制律可使网络控制系统均方指数稳定。
The paper proves that optimal controllers can stabilize the exponentially mean square of networked control systems.
从而将两点边值问题解序列的有限次迭代结果作为系统的次优控制律。
Some finite iterative result of the two-point boundary value problem sequence is taken as a suboptimal control law of the system.
使用符号运算方法设计了系统闭环控制律和大攻角下的过失速控制律。
The control laws of the inner closed loop system and post stall maneuver are obtained through using symbol operations design.
给出了最优控制律的存在唯一性条件，并提出了最优控制律的设计算法。
The conditions of existence and uniqueness of the optimal control law is given and an algorithm of solving the optimal control law is proposed.
所设计的控制律兼具连续控制律与非连续控制律的优点，动态品质优良。
The control law designed which dynamic quality was very well had characteristics both of continuous and non-continuous control laws.
进行了空速保持、高度保持、航向保持和转弯控制等控制律的详细分析。
The control principle of airspeed keeping, altitude keeping, course keeping and swerve control is analyzed, too.
基本控制律采用非线性动态逆方法设计，神经网络用于对逆误差进行重构。
The base control law is designed in dynamic inversion and neural networks are used to reconstruct inversion error.
为此，本文进行了飞机总体设计中的飞行控制律模型设计与应用方法研究。
Thus, an approach of Flight Control Law (FCL) model design and application for aircraft conceptual design is researched.
其中长周期运动控制律设计时，结合了喷气推力控制来辅助偏置动量控制；
When design the control method of long-time cycle movement, whiff thruster is used to assistant the control system.
说明了这种控制律可以通过选取控制输入使得最大概率预报器作出的预报为零得到。
This control law is shown to comprise a maximal probability predictor, and control input is chosen to make the prediction zero.
给出了前馈-反馈最优控制律的存在唯一性条件，并提出了最优控制律的实现算法。
We give the existence and uniqueness conditions of the feedforward and feedback optimal control law, and present an actualizing algorithm of solving the optimal control law.
给出了前馈-反馈最优控制律的存在唯一性条件，并提出了最优控制律的实现算法。
We give the existence and uniqueness conditions of the feedforward and feedback optimal control law, and present an actualizing algorithm of solving the optimal control law.
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