Titlebook: Identification of Multivariable Industrial Processes; for Simulation, Diag Yucai Zhu,Ton Backx Book 1993 Springer-Verlag London 1993 Dynami

催眠藥

船員

打火石

Introduction, may characterize the system by input/output (cause and effect) relations. What constitutes a . depends on the point of view of the observer. The . may be, for example, an amplifier consisting of electronic components, or a control loop including that amplifier as one of its parts, or a chemical pro

palliate

武器

occult

Identification by the Least-Squares Method,r determining the orbits of planets. Since then this method has become a major tool for parameter estimation using experimental data. Most existing parametric identification methods can be related to the least-squares method. The method is easy to comprehend and, due to the existence of a closed sol

織布機(jī)

Extensions of the Least-Squares Method,of the parameters of a transfer operator or difference equation model are biased (not consistent); and the model fit in the frequency domain is not always good, for the high frequencies are over-emphasized. In the last two decades, much research has been done to modify and to extend the LS method in

Cardiac-Output

MIMO Process Identification: A Markov Parameter Approach,the prediction error methods. We have seen that the properties of the LS method and those of the prediction error methods are complementary: the LS method is numerically simple and reliable, but model quality is low due to the bias of the estimate; the prediction error methods can give accurate esti

懶惰人民

Identification for Robust Control; SISO Case,dentification of industrial processes, undermodelling and disturbances are the main causes of model errors. In the previous decade, robust control theory has been proposed and developed; cf. Zames (1981), Doyle (1982), Vidyasagar (1985) and Morati and Zafiriou (1989). The advantage of robust control

modifier