研究了一类可以抑制切换时刻输出跳跃的多模型切换控制器的设计问题。
The problem of designing a switching controller for chattering attenuation in multi-model systems is considered.
研究了一类可以抑制切换时刻输出跳跃的多模型切换控制器的设计问题。
The problem of designing a switching controller for chattering attenuation in multi-model system is considered.
由于不再需要设计多个控制器，因此避免了常规多模型切换控制中抖动的产生。
Because of single robust controller, the switching chattering in traditional multi-model control was avoided.
针对切换控制中模型匹配准则的确定问题，提出了一种基于模型有效匹配的多模型切换控制算法。
In order to determine the model matching index of switching control, a multiple models switching control algorithm based on effective model matching was presented.
采用了具有积分性质的切换指标函数作为切换法则和最小方差的控制方法构成了多模型自适应控制器。
A switching function with integral property and minimum variance algorithm are used to set up the multiple model adaptive controller.
给定一个指标切换函数，基于多个自适应模型控制器和给定的指标切换函数构成多模型自适应控制器。
Based on the multiple controllers, a multiple model adaptive controller can be formed by using an index switching function.
运用变结构滑模控制理论和多模型切换，使车辆转向控制具有良好的跟踪性能和鲁棒性。
The use of variable structure control theory and multiple-model conversion makes the vehicle steering control have favorable tracking capability and robustness.
针对非线性时变系统在自适应控制过程中瞬态响应差的问题，提出了一种基于多模型自适应控制的模型切换算法。
A model switching algorithm based on multi-model adaptive control is presented to solve the problem of poor transient response in the adaptive control of nonlinear time-varying system.
把多包传输网络控制系统建模为具有一定切换规则的线性切换系统模型。
The NCS is modelled as models of linear switched control systems under certain switching sequences.
提出了不确定非线性系统多模型预测控制的新方法，它结合了针对非线性的基于系统输出的切换方法和针对不确定性的模型切换方法。
For the uncertain nonlinear system, the multiple-model predictive control is studied which combines the switching method for the nonlinearity and the one for the model uncertainty.
为了解决切换多模型预测控制的抖动问题，提出了加权多模型模糊预测控制。
To solve the problem of perturbation of witching multi-model predictive control, weighted multi-model fuzzy predictive control is put forward.
为了解决切换多模型预测控制的抖动问题，提出了加权多模型模糊预测控制。
To solve the problem of perturbation of witching multi-model predictive control, weighted multi-model fuzzy predictive control is put forward.
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