摘要
本文提出了同时估计线性多变量系统所有参数的联合辨识算法(CIA),并用随机过程理论分析了算法的收敛性。与子系统辨识算法(SSIA)相比,CIA的计算量要小得多。各输出间存在相互作用噪声时的辨识问题通过使用递推广义增广最小二乘法(RGELA)得到解决。数字仿真结果表明了CIA的有效性。
In this paper, the combined identification algorithm (CTA) for linear multivariable systems is presented which can simultaneously estimate all parameters of the whole system. The convergence of CIA is analyzed by means of stochastic process theory. The problem of identification in the presence of interactive noises at different outputs is solved by using the recursive generalized extended least-squares method. Compared with subsystem identification algorithm, CIA has much less amount of the calculation. The simulation examples are included.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
1992年第5期545-550,共6页
Control Theory & Applications
关键词
参数估计
联合辨识算法
多参数控制
multivariable system
parameter estimation
generalized extended least squares
combined identification algorithm
