STUDY ON CONTINIOUS-TIME SYSTEM IDENTIFICATION IN VIEW OF KNOWLEDGE OF PHYSICAL AND CHEMICAL LAWS

近年来，随着鲁棒控制理论的发展，模型不确定性下的系统辨识问题引起了人们的广泛关注。由于微机技术的进步，在较小的采样周期内进行处理已成为可能，预计估计精度将有相当大的提高。本文主要从（1）预滤波器作为抗混叠滤波器对系统辨识的影响（2）确定模型阶数的方法的发展（3）鲁棒控制系统辨识方法的评价（4）多变量系统的推广（5）非线性系统方法的发展等方面进行了研究，目的是发展适合于控制器设计的辨识方案。从模型的质量取决于模型在适当的频率范围内具有充分跟踪特性的能力，以及预滤波器不仅是数据处理，而且是将被控对象的先验知识带入模型的观点来看。我们完全表明，在这项研究中，识别计划可以适用于大规模，复杂的真实的系统，通过将它们扩展到多变量系统和发展非线性系统识别，考虑到植物的物理信息。

Recently, much attention has been attracted for system identification, stimulated by develepment of robust control theory in the presence of model uncertainty. Considerable improvement of estimation accuracy is expected because processing in smaller sampling period has become possible due to the progress of the technology around microcomputer. We have studied mainly from the viewpoint of(1) effects of prefileter suce as antialias filter to system identification(2) development of the method to determine the order of a model(3) evaluation of system identification methods for robust control(4) extension to multivariate systems, and(5) development of methods for nonlinear systems.Our intention has been development of identification scheme suited well for controller design, from standpoint that the quality of the model depends on that the model has capability to trace adequately the characteristics in proper frequency range, and that prefilter is not only data processing but also ones taking a priori knowledge of the plant into the model. We showed totally in this research, that the identification schemes can be applied to large scale, complex real systems by extending them to multivariate systems and developing nonlinear systems identification, taking account of physical information of the plant.