与经典的最小二乘法相比，共优点是能有效地抑制非整次谐波误差对模型参数估计的影响。
Comparing with the least squares method, the advantage of this approach in that the influence of non-integer harmonic errors on the estimate of model parameters has been effectively restricted.
提出了席位公平分配的最小极差法及其数学规划模型，比较分析了多种不同席位分配方法，并提出了非完全分配的概念及其数学模型。
This paper presents the method of minimum difference of poles on fair allocation of seats and its mathematical programming model, and analyses several methods of allocation of seats number.
本文基于非参数回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。
Based on the locally kernel weighted least squares fit of the nonparametric regression models, this paper presents the nonparametric testing method for nonlinear cointegration.
本文基于非参数可加回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。
Based on the local kernal weighted least squared fit of the nonparametric and additive regression model, this paper presents the nonparametric testing method for nonlinear cointegration.
探讨了关于非最小相位系统的参考模型自适应控制系统（MRACS）的一种设计方法。
This paper is concerned with a design of a model refenrence adaptive control system (MRACS)for a nonminimum phase system.
水轮机调速系统是典型的具有非最小相位、非线性、时变特性的复杂控制系统，难以建立精确的数学模型。
To the question of the hydraulic turbine regulating system, this paper discusses fuzzy neural network control (FNNC) based on the character of fuzzy logic and neural network theory.
研究直升机悬停状态时其动力学模型非最小相位且不稳定特性的设计问题。
A study on the method of design is presented for helicopter hover with nonminimumphase unstable characteristics.
采用了非最小相位系统参数模型转换为参数模型的控制器的设计。
Using the non minimum phase system parameter model transformation of the model for the controller design.
针对一类不确定的离散时间非线性非最小相位动态系统，提出了一种基于神经网络和多模型的直接自适应控制方法。
A direct adaptive control approach is proposed for a class of uncertain discrete time nonlinear non-minimum phase dynamical systems.
建立了磁浮轴承的近似非最小相位传递函数模型，并基于此模型设计了保证系统稳定的闭环控制器。
An approximate non-minimum phase transfer function of magnetic suspension bearing is established, on the basis of that, a closed-loop controller is designed and makes the whole system stable.
模型预测控制对模型精度要求不高，对模型失配、非最小相位系统、不确定干扰的影响具有较强的鲁棒性，具有较高的控制性能。
Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance.
模型预测控制对模型精度要求不高，对模型失配、非最小相位系统、不确定干扰的影响具有较强的鲁棒性，具有较高的控制性能。
Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance.
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