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双线性系统

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New parameter estimation Markov recursive algorithm for continuous stochastic linear system and bilinear system is proposed.

基于小波变换的连续随机线性和双线性系统参数辨识Markov方法分析研究了连续维纳过程在小波变换下的统计特性,给出了维纳过程的离散小波变换系数所构成的离散随机过程的协方差矩阵计算和估计方法,基此提出了线性和双线性连续随机系统参数辨识的Markov估计方法及其递推算法。

Singular bilinear system, different from a linear singular system, is a kind of nonlinear singular system. Control theories and applications of nonlinear systems have always been a hot research focus due to their potentials.

广义双线性系统是最接近广义线性系统的一类广义非线性系统,非线性系统的理论分析与应用一直是控制领域研究的热点与难点。

The proof of the relevant theory for the discrete singular bilinear system may be regarded as the extension of the normal discrete bilinear system.

对于离散广义双线性系统有关理论的证明,可以看作是正常离散双线性系统的拓广。

Simulation studies of the dissolved oxygen control in wastewater treatment and pH control in a reactor show that the algorithms given in the thesis have good performance, and the algorithms are simple and easy to use and need fewer measured parameters in comparison with Goodwin's method of bilinear system adaptive control.

将本文的双线性系统自适应控制方法,用于废水处理中的溶氧过程控制和pH值控制的实例仿真研究表明,本文算法具有良好的动态性能,和Goodwin所采用的双线性自适应控制方案相比,具有所需的测量参数少、简单、易于实现等优点。

The algorithm combines bilinear and linear terms of I/O bilinear system, and constitutes an ARIMA model analogous to linear system.

针对一类输入-输出双线性系统,提出了一种双线性系统的广义预测控制算法。

For general discrete bilinear system, this paper proposed a stability criteria which is sufficient for systems with linear feedback. The smallest attracting range is also obtained. Based on the criteria, a simple control law is proposed to guarantee the uniformly asymptotically stability of zero state.

对于一般离散双线性系统,本文提出了系统在线性反馈下的稳定性判据和最小吸引域,并给出了一种简单的控制方案,保证闭环系统在原点的一致渐近稳定性。

Being a subclass of nonlinear systems, bilinear system is useful to approximate a class of nonlinear systems and implement predictive control in many circumstances.

由于在实际中很多非线性工业过程可由双线性系统近似,因此对此类系统我们选择使用双线性预测控制策略。

The new problems and challenges appearing in the nonlinear applicationes are solved, which makes subspace identification more applicable to the modeling and control of industrial process. With regards to bilinear system, a major drawback is that the subspace identification methods induce enormous dimension of the data matrices, which grows exponentially with the increase of the model order.

针对两类特殊的非线性系统,双线性系统和分段线性系统,从子空间辨识的设计与实现出发,提出新的辨识算法,解决子空间方法应用于非线性系统辨识遇到的新问题,使得子空间方法在工业过程的辨识与建模中具有更强的实用性。

Without using Lie derivative and Lie bracket operation of differential geometry , we only use the algebra method to give a sufficient condition of single input exact feedback linearizable bilinear systems.

摘 要 研究了单输入的双线性系统的精确线性化及其鲁棒控制器设计问题,避免了用微分几何的李导数、李括号的复杂运算,只用纯代数的方法给出了一般单输入双线性系统精确线性化的充分条件。

Especially for multifrequence problems, both the order for the approximation of nonlinear functions and the iterative numbers for neural network learning will be decreased by several times.

利用这种新方法可以直接分析、辨识线性系统、双线性系统的稳定性和未知参数,并可直接求取性能指标下的最优控制律。

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