针对一类关联项的上界是高阶多项式的关联大系统，设计了一种新的分散自适应模糊控制方法。
In this paper, it develops a novel decentralized adaptive fuzzy control for a class of large-scale nonlinear systems with higher order interconnections.
针对不确定分段线性系统，将最优控制设计问题转化成最优控制性能上界的优化问题及性能下界的求取问题。
The optimal control design for the uncertain piecewise linear system has been converted to the problem of optimizing upper bound and seeking lower bound of the optimal control performance.
应用李亚普诺夫直接法，提出了一种基于不确定项上界的连续型鲁棒控制器设计方法。
Applying Lyapunov direct method, a design method of continuous robust controller is proposed based on the upper bounds of the uncertainties.
针对满足一定条件的一类不确定部分上界不确知的系统，提出了一种参数自适应积分滑模控制策略。
This paper presents an integral sliding mode control with adaptive parameters for a class of systems satisfying some conditions when the upper bounds of uncertainties are unknown.
在模型的部分不确定上界未知时修改了控制器，并得出全局渐近收敛的结果。
Moreover, when the upper bounds of some uncertainties are unknown, the control is revised to guarantee globally asymptotical stabilization.
该控制律使系统闭环稳定，且系统对扰动输入的增益不超过某一人为设定的上界。
The control law makes the system closed-loop stable, and the gain of the system for the disturbance input will be limited under a scheduled upper - bound.
引入凸优化算法，求解使闭环系统渐近稳定且性能指标上界最小的最优控制器参数。
The convex optimization algorithm was used to get the minima upper bound of performance cost and parameter of optimal minimax controller.
该方法不要求的先验知识的控制增益的符号和的上界和下界的先验已知的死区模型参数。
The approach does not require apriori knowledge of the sign of the control gain and the upper bound and lower bound of dead zone model parameter to be known apriori.
该方法不要求的先验知识的控制增益的符号和的上界和下界的先验已知的死区模型参数。
The approach does not require apriori knowledge of the sign of the control gain and the upper bound and lower bound of dead zone model parameter to be known apriori.
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