tailieunhanh - Tóm tắt về giảm bậc cho các mô hình: một giải pháp mang tính bình phẩm.

Tóm tắt về giảm bậc cho các mô hình: một giải pháp mang tính bình phẩm. Điều khiển học (tiếng Anh: cybernetics) là khoa học về việc điều khiển, thu thập, truyền và xử lý thông tin, thường bao gồm liên hệ điều chỉnh ngược trong các cơ thể sống, trong máy móc và các tổ chức và các kết hợp của chúng (thí dụ hệ thống kỹ thuật xã hội, các máy móc do máy tính điểu khiển, chẳng hạn robot) | Tạp chí Tin học và Điều khiến học T. 16 s. 1 2000 1-14 BRIEF ON ORDER-REDUCTION FOR MODELS A CRITICAL SURVEY NGUYEN THUY ANH NGUYEN NGOC SAN Abstract. A review on different methods for obtaining reduced-order models for complex high-order systems is briefly made. A critical comparison is made of the extent to which the models obtained from the optimal projection equations adopting state - optimization method proposed by authors are seen retaining the physical significance of the original modeled states. 1. INTRODUCTION In most practical situation of system control a faừly complex high-order often makes a difficulty in understanding the behavior of the system as well as in controlling the system can be accomplished with a great easy by using suitably selected low-order model having the important characteristics of the model. During the last 40 years a great deal of research work has been carried out for solving the order-reduction problem as would be evident from the fact that more than 500 research papers have been so far published proposing different approaches on the subjects. However practically all of the proposed approaches are seen to belong to one of three main groups. The first groups of methods approaches attempts to retain the important eigenvalues of the system-model and then obtain the corresponding parameters of the low-order model in such a manner that the response of the low-order model to certain inputs is a close approximation to that of the original model. The earliest methods of order-reduction for models proposed by Marshall 27 Davison 9 Mitra 28 and Aoki 3 are belonged to the first group. However Hickin and Sinha 15 have shown that the first three methods may be regarded to be special cases of the aggregation method proposed by Aoki 3 The second group is based on an optimum manner indifferent of the eigenvalues location of the original model. Anderson 1 has proposed a geometric approach based on orthogonal projection for obtaining a low-order .