Large-Scale Dynamic Systems
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NASA SP-371 LOAN COPY: RETUR AFWU TECHNICAL LIE ] •KIRTLAND_AFB, N. LARGE-SCALE DYNAMIC SYSTEMS A seminar workshop held at UTAH STATE UNIVERSITY Logan, Utah August 12-16, 1974 A: ftppriv/cn NATIONAL AERONAUTICS AND SPACE ADMINISTRATION „ - At" * * ». NASA/SP-371 TECH LIBRARY KAFB, NM •v , "I LARGE-SCALE DYNAMIC SYSTEMS, proceedings of the Utah State University—Ames Research Center Seminar Workshop <rn-t>argv»Scith Dynamic—Syst-ems, held at Utah State UniverfTtyrL&ganr&tnh, August 12-16, 1974 ( . Prepared by Ames Research Center Scientific and Technical Information Office 1975/ NATIONAL AERONAUTICS AND SPACE ADMINISTRATION Washington, D.C. For sale by the National Technical Information Service Springfield, Virginia 22151 $7.25 FOREWORD The Utah State University — Ames Research Center Seminar Workshop on Large-Scale Dynamic Systems was held August 12-16, 1974, at Logan, Utah. The workshop was supported by Ames Research Center. These proceedings contain the papers presented at this workshop. I wish to thank the participants for their cooperation in arranging the conference and for their promptness in supplying manuscripts. The support and encouragement given by Professor Ralph Johnson, Dean of the College of Science, and Professor Lawrence O. Cannon, Head of the Depart- ment of Mathematics, are gratefully acknowledged. Special thanks are due Larry Sharp, who handled the many small details during the workshop, and also Wanda Sayer and Lynette Robinson, who cheerfully completed the almost impossible task of typing the manuscripts and rough drafts of the proceedings. CLYDE F. MARTIN m PARTICIPANTS Masanao Aoki University of Illinois Michael Athans Massachusetts Institute of Technology C. Y. Chong Georgia Institute of Technology Kai-Ching Chu IBM, Thomas J. Watson Center Luigi Cicolani Ames Research Center Hermann W. Dommell University of British Columbia Brian Doolin Ames Research Center Y. C. Ho Harvard University Trevor Hughes Utah State University Raymond Jacquot University of Wyoming Clyde Martin Utah State University John Richardson Case Western Reserve University Leonard Roberts Ames Research Center Larry Sharp Utah State University Dragoslav Siljak Santa Clara University Glen Smerage Utah State University Bruce Watkins Utah State University IV TABLE OF CONTENTS Page Foreword iii List of Participants iv Summary 1 Brian Doolin and Clyde Martin Ames Research Center and Utah State University Simulation of Large-Scale Dynamic Systems 7 Leonard Roberts, Ames Research Center Hierarchial Models of Very Large Problems, Dilemmas, Prospects, and an Agenda for the Future 23 John M. Richardson, Jr., Case Western Reserve University An Informal Paper on Large-Scale Dynamic Systems 49 Y. C. Ho, Harvard University Analysis of Large-Scale Water Resources Systems 63 A. Bruce Bishop and Trevor C. Hughes, Utah State University Survey of Decentralized Control Methods 101 Michael Athans, Massachusetts Institute of Technology Feedback Control of a Single Irrigation Canal Reach 113 Raymond G. Jacquot, University of Wyoming Analysis of Large Power Systems 119 Herman W. Dommel, University of British Columbia Decentralized Regulation of Dynamic Systems 131 Kai-ching Chu, IBM Watson Research Center Large-Scale Systems: Complexity, Stability, Reliability 147 D. D. Siljak, University of Santa Clara Digital Simulation of V/STOL Aircraft for Autopilot Research 163 L. S. Cicolani and George Meyer, Ames Research Center Some Notions of Decentralization and Coordination in Large-Scale Dynamic Systems ... 185 C. Y. Chong, Georgia Institute of Technology Some Aspects of Control of a Large-Scale Dynamic System 195 Masanao Aoki, University of Illinois A SUMMARY OF THE PROCEEDINGS OF THE UTAH STATE UNIVERSITY AMES RESEARCH CENTER SEMINAR WORKSHOP ON LARGE SCALE DYNAMIC SYSTEMS* Brian Doolin Ames Research Center and Clyde Martin Utah State University PURPOSE AND APPROACH This seminar workshop was held on the campus of Utah State University during the week of August 12—16, 1974. The general purpose of the workshop was to discern classes of large-scale dynamic systems, with no attempt to solve their problems. It was felt that such a workshop was necessary to help bridge the gap between the theory that power has been substantiated in small problems where analytic models are readily verified and that required for the almost incomprehen- sibly large problems in aeronautics, economics, natural resource management, and many other fields which modern computational capability has emboldened researchers to face. The approach adopted for the workshop contained three elements. One element was to examine three major examples of large-scale systems. It was hoped that an examination of these examples would result in a transfer of knowledge so that control theorists would gain a broader view of large systems and a knowledge of how the problems are being successfully handled. Prin- ciples or properties common to large systems could be extracted. Finally, it was hoped that study- ing the examples in the context of modern control theory would present directions of research that would lead to useful methods of analysis and synthesis. The remarks that follow show the workshop' was somewhat successful in realizing these hopes. The three technical areas covered in the examples were aeronautics, water resources, and electric power. Aeronautics technology was described in two papers. The opening paper reviewed the growing use, in the development of aircraft, of computer-based methods to coordinate pro- cedures and concepts from several technical disciplines. The second illustrated the complexity in one of the simulations. Water resources management was also discussed in two papers: the first described the problem in general and the second illustrated the dynamic analysis of a canal reach. The development of analysis and its present status in the electric power distribution industry were covered in a single paper. 'Supported by NASA Grant No. NSG-2022. A second element of the approach of the workshop was to review control theory relevant to large-scale systems. This was accomplished by the control theorists who explained the development of their ideas. The provocative paper by John Richardson, which discussed methodology in terms of examples from water eutrophication and world modeling, could be categorized as either example or theory. The third element of the approach was a discussion period. Each afternoon, the participants freely aired their thoughts evoked by the papers presented and by restatements of the aims of the workshop. WORKSHOP RESULTS The most significant result of the workshop was the active transference of ideas and concepts during the afternoon discussion periods. Naturally, there was some fundamental disagreement on the significance of certain technical points, but this reflects the fact that the techniques to be used in the study of large-scale dynamic systems are not yet known. Though the existence of large-scale systems as objects for understanding and management was unanimously affirmed, there was no consensus on a definition. Nor were acceptable quantitative measures of scale proposed. Various general properties from different points of view could be ascribed to them. From the viewpoint of developing analytic models, a system is large when its input-output behavior cannot be understood without curtailing it, partitioning it into modules, and aggregating its modularized subsystems. From a systems viewpoint, a system is large if it exceeds the capacity of a single control structure. This circumstance arises when there is too much data for a single-decision element to process in a timely fashion. A common solution is to decentralize the control structure at some cost in performance but with gains in reliability. Finally, there was concern that analytic models of some large systems could not be used to predict behavior over intervals of time much longer than required for observation. One reason for the concern was the experience of numerical difficulties due to the size of the model. Its predicted behavior would be accepted only if accompanied by some measure of error propagation. Another reason for the concern was that, when human response is involved, the model could not be made sufficiently complete. The discussions led to a thorough review of the state of the theoretical knowledge of decen- tralized and connected systems. Centralization versus decentralization appears to be a major ques- tion in the control of large systems. It is now clear that quadratic optimality of linear systems implies centralized control and information at least under conditions of instantaneous and perfect transmission of information. Under real conditions, transformation and information is usually neither instantaneous nor perfect. Then decentralization offers the potential for increased reliability (in the sense of immunity from catastrophe) and subsystem stability. Sometimes, however, decen- tralization decreases the overall reliability by increasing the time required to detect failure. Then how to trade performance for reliability becomes obscure. Reliability has become an active area of research and one for which major results are almost certain to be obtained soon. Although theory is developing on centralization versus decentralization and on optimization, reliability, and connective stability, there is a clear need for real numerical examples. If the control theorists reached a consensus, it was that there is a strong continuing need to study particular examples in detail, both simple