- Email: [email protected]
Concise encyclopedia of modelling & simulation
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Book Reviews
/~strrm, K. J. and T. Bohlin (1965). Numerical identification of linear dynamical systems from normal operating records. IFAC Symposium on Self-adaptive Systems, Teddington, U.K. Hannah, E. J. and M. Deistler (1988). The Statistical Theory of Linear Systems. J. Wiley & Sons, New York, 1988. Helmicki, A. J., C. A. Jacobson, and C. N. Nett (1991). Control oriented system identification: a worstcase/deterministic approach in H~. IEEE Trans. Aut. Control, 36, 1163-1176. LaMarie, R. O., L. Valavani, M. Athens and G. Stein (1991). A frequency domain estimator for use in adaptive control systems. Automatica, 27, 23-38. Ljung, L. (1985). On the estimation of transfer functions. Automatica, 21, 677-690. Ljung, L. (1987). System Identification: Theory for the User. Prentice-Hall, Englewood Cliffs, NJ. Ljung, L. (1991). Issues in system identification. IEEE Control Systems Magazine, 11, 25-28. Ljung, L. and K. Glover (1981). Frequency domain versus time domain methods in system identification. Automatica, 17, 71-86. Ljung, L. and T. S6derstr6m (1983). Theory and Practice of Recursive Identification. M.I.T. Press, Cambridge, MA. Parker, P. J. and R. R. Bitmead (1987). Adaptive frequency response identification. Proc. 26th CDC, Los Angeles, CA, pp. 348-353.
Sidman, M., F. DeAngelis, and G. Verghese (1991). Parameteric system identification on logarithmic frequency response data. IEEE Trans. Aut. Control, AC-36, 1065-1070. S6derstrrm, T. and P. G. Stoica (1989). System Identification. Prentice-Hall International, Hemel Hempstead, U.K.
About the reviewer Bo Wahlberg was born in Norrkrping, Sweden, in 1959. He received the M.S. degree in 1983, the Licentiate degree of Technology in 1985 and the Ph.D. degree in 1987 from Link6ping University, LinkiSping, Sweden. He has held visiting positions at the University of Cambridge, U.K., University of Newcastle, Australia, Australian National University, Australia and Delft University of Technology, The Netherlands. From 1989 to 1991, he was a Research Associate at Link6ping Univeristy, Linkt~ping, Sweden. In December 1991, he became Professor of the Chair of Automatic Control at the Royal Institute of Technology, Stockholm, Sweden. His research interests include system identification, time series analysis and signal processing. Professor Wahlberg received the Hugo Schuck Best Paper Award of the 1986 American Control Conference. He is an Associate Editor for Automatica, in the area of parameter estimation and adaptive control.
Concise Encyclopedia of Modelling & Simulation* D. P. Atherton and P. Borne (Editors) Reviewer: STUART H. STARR The MITRE Corporation, McLean, VA 22101, U.S.A. WITHIN THE FAST five years there has been a resurgence in interest in the subject of modelling and simulation, fueled in part by the ongoing revolution in computer and communications technology. This increased interest has been manifested by major initiatives by the defense community in the areas of synthetic environments and advanced distributed simulation, and by the commercial sector in the area of virtual reality. Consequently, the appearance of this concise encyclopedia of modelling and simulation comes at an expeditious moment. This volume has much to offer to the practicing engineer, researcher and postgraduate student on modelling and simulation from a control theoretic perspective; unfortunately, it does not fully respond to the needs of the total audience, particularly in those areas where modelling and simulation are experiencing the most explosive growth. To put the subject volume in context, this review first discusses what the encyclopedia seeks to achieve and evaluates its success in realizing these objectives. It then goes on to identify and discuss those areas that are beyond the scope of the current volume as a challenge to future editions or additional volumes. The Concise Encyclopedia of Modelling & Simulation follows from the landmark Systems & Control Encyclopedia issued by Pergamon Press in 1987. In its wake, Pergamon Press has issued seven concise encyclopedias in a variety of applied disciplines (e.g. environmental systems, software engineering, traffic and transportation systems). This eighth concise encyclopedia purports to be a comprehensive
* Concise Encyclopedia of Modelling & Simulation edited by D. P. Atherton and P. Borne. Pergamon Press, Oxford U.K. ISBN 0-08-036201X. £140.00, $280.00.
reference work covering all aspects of modelling and simulation. To this end, it provides approximately 170 alphabetically arranged entries. However, it should be noted that approximately 40% of the entries are relatively terse definitions of key phrases or concepts. The more extended entries emphasize the use of modelling and simulation to assess the behavior of physical processes using mathematical models to the extent practical. Consideration is given to a broad spectrum of systems including aeronautics and space, biological and biomedical, chemical engineering, power plants, ship dynamics, and traffic and transportation. In all cases there is a useful cross-coupling/referencing system, coupled with an extensive subject index, that makes it relatively easy to navigate through the volume. This, in itself, is testimony to the diligence of the encyclopedia's editors, D. P. Atherton and P. Borne. The strengths of this volume are considerable. It draws upon many of the major figures in the field of automatic control for articles that are concise and often elegant. In several cases, key subjects are treated in depth from multiple, reinforcing perspectives. For example, there are 13 entries on the subject of identification, with the contributions of L. Ljung (on the basic problem, least squares method, maximum likelihood method, recursive methods, and time-domain methods) and G. C. Goodwin (on experiment design) being particularly notable. In addition, there are interesting and useful treatments on the nature and use of Petri Nets (by T. Murata and J. P. Bourey et al.), state space modelling (by J. P. Richard and P. Borne, and T. Kailath) and the challenges posed by validating simulation models (by R. G. Sargent). The last area, however, suggests one of the book's shortfalls. There are four entries on the subject of validation (by three contributors) and each contributor defines the term somewhat differently. In many other cases there is a disappointing imprecision in the introduction and consistent use of definitions.
Book Reviews However, it must be noted that for a work that claims to be "a comprehensive reference work covering all aspects of modelling and simulation" there are disconcerting weaknesses and voids. Although there is implicit treatment of a variety of important ancillary subjects (e.g. simulation languages, data dictionaries and repositories, software engineering), their addressal is not commensurate with contemporary interest and activity. For example, there is a wide-spread debate in the modelling and simulation community about the relative strengths and weaknesses of A D A and C + + ; however, little or any insight into the subject could be gleaned from the pages of this volume. The greatest weakness of the volume stems from its failure to address a variety of issues that have become central to research in modelling and simulation. Recently, the U.S. defense community has defined three classes of modelling and simulation: live modelling and simulation, involving instrumented operations with live people and real equipment in the field (e.g. instrumented mock combat at facilities such as the U.S. Army's National Training Center); constructive modelling and simulation, involving the use of classical mathematical models or analytical tools, often implemented on computers; and virtual modelling and simulation, involving systems and personnel in simulators performing simulated functions (e.g. users of aircraft simulators). A vision has been articulated of synthetic environments in which examples of each of these classes would be joined together, seamlessly, and accessible from any point on the globe. Ultimately, such a tool would be used to support a wide variety of activities including operations (e.g. training, the formulation and assessment of alternative concepts of operations) and the acquisition of new systems (e.g. support to technology assessment, prototyping of new concepts). To allow maximum utility and flexibility it is projected that these synthetic environments will be constructed from affordable, reusable components and interoperate through an open systems architecture. The implications of this vision are extraordinary in multiple dimensions. It will require, inter alia, breakthroughs in the technology underlying modelling and simulation (e.g. in the representations of human behavior, including automated forces, and the depicted environment), significant
1623
improvements in supporting systems (e.g. very wide band communications links featuring multicasting; enhanced graphi~ rendering), and innovations in software engineering. Associated with all of these needs is the requirement for an appropriate overreaching architectural vision and associated standards and protocols that the community can employ. Although these issues dominate the interests of a major segment of the modelling and simulation community, they are barely hinted at in the current volume. This suggests that the concise encyclopedia's claim to cover all aspects of modelling and simulation falls considerably short of the mark. In summary, the book in question brings to mind one of the oldest metaphors in literature: the partially filled glass. In this case, it must be said that the liquid that is present has been carefully distilled and is quite nourishing, particularly to the practicing control theorist. However, the contemporary practitioner of modelling and simulation is apt to note the considerable void that is present in the glass and wish for a second edition that slakes that thirst. About the reviwer
Stuart H. Starr received a B.S. in Electrical Engineering from Columbia University, New York, in 1963, and his M.S. and Ph.D. in Electrical Engineering from the University of Illinois, Urbana, Illinois, in 1965 and 1969, respectively. He is Director of Plans, Washington Group, The MITRE Corporation, in McLean, Virginia. His research interests include the development and application of methodologies (with emphasis on the use of modelling and simulation) to plan and assess large, complex systems. Prior to joining MITRE in 1985, he was Assistant Vice President for C3I Systems at M/A-COM Government Systems, Director of Long Range Planning and Systems Evaluation for the Office of the Assistant Secretary of Defense (C3I), and Senior Project Leader at the Institute for Defense Analyses. He is a member of Phi Beta Kappa and Pi Mu Epsilon, a senior member of both the IEEE and AIAA, and a frequent participant in special studies and scientific advisory boards (e.g. consultant to OSD Net Assessment; member of Senior Advisory Group, Office of Technology Assessment).
Book Reviews
/~strrm, K. J. and T. Bohlin (1965). Numerical identification of linear dynamical systems from normal operating records. IFAC Symposium on Self-adaptive Systems, Teddington, U.K. Hannah, E. J. and M. Deistler (1988). The Statistical Theory of Linear Systems. J. Wiley & Sons, New York, 1988. Helmicki, A. J., C. A. Jacobson, and C. N. Nett (1991). Control oriented system identification: a worstcase/deterministic approach in H~. IEEE Trans. Aut. Control, 36, 1163-1176. LaMarie, R. O., L. Valavani, M. Athens and G. Stein (1991). A frequency domain estimator for use in adaptive control systems. Automatica, 27, 23-38. Ljung, L. (1985). On the estimation of transfer functions. Automatica, 21, 677-690. Ljung, L. (1987). System Identification: Theory for the User. Prentice-Hall, Englewood Cliffs, NJ. Ljung, L. (1991). Issues in system identification. IEEE Control Systems Magazine, 11, 25-28. Ljung, L. and K. Glover (1981). Frequency domain versus time domain methods in system identification. Automatica, 17, 71-86. Ljung, L. and T. S6derstr6m (1983). Theory and Practice of Recursive Identification. M.I.T. Press, Cambridge, MA. Parker, P. J. and R. R. Bitmead (1987). Adaptive frequency response identification. Proc. 26th CDC, Los Angeles, CA, pp. 348-353.
Sidman, M., F. DeAngelis, and G. Verghese (1991). Parameteric system identification on logarithmic frequency response data. IEEE Trans. Aut. Control, AC-36, 1065-1070. S6derstrrm, T. and P. G. Stoica (1989). System Identification. Prentice-Hall International, Hemel Hempstead, U.K.
About the reviewer Bo Wahlberg was born in Norrkrping, Sweden, in 1959. He received the M.S. degree in 1983, the Licentiate degree of Technology in 1985 and the Ph.D. degree in 1987 from Link6ping University, LinkiSping, Sweden. He has held visiting positions at the University of Cambridge, U.K., University of Newcastle, Australia, Australian National University, Australia and Delft University of Technology, The Netherlands. From 1989 to 1991, he was a Research Associate at Link6ping Univeristy, Linkt~ping, Sweden. In December 1991, he became Professor of the Chair of Automatic Control at the Royal Institute of Technology, Stockholm, Sweden. His research interests include system identification, time series analysis and signal processing. Professor Wahlberg received the Hugo Schuck Best Paper Award of the 1986 American Control Conference. He is an Associate Editor for Automatica, in the area of parameter estimation and adaptive control.
Concise Encyclopedia of Modelling & Simulation* D. P. Atherton and P. Borne (Editors) Reviewer: STUART H. STARR The MITRE Corporation, McLean, VA 22101, U.S.A. WITHIN THE FAST five years there has been a resurgence in interest in the subject of modelling and simulation, fueled in part by the ongoing revolution in computer and communications technology. This increased interest has been manifested by major initiatives by the defense community in the areas of synthetic environments and advanced distributed simulation, and by the commercial sector in the area of virtual reality. Consequently, the appearance of this concise encyclopedia of modelling and simulation comes at an expeditious moment. This volume has much to offer to the practicing engineer, researcher and postgraduate student on modelling and simulation from a control theoretic perspective; unfortunately, it does not fully respond to the needs of the total audience, particularly in those areas where modelling and simulation are experiencing the most explosive growth. To put the subject volume in context, this review first discusses what the encyclopedia seeks to achieve and evaluates its success in realizing these objectives. It then goes on to identify and discuss those areas that are beyond the scope of the current volume as a challenge to future editions or additional volumes. The Concise Encyclopedia of Modelling & Simulation follows from the landmark Systems & Control Encyclopedia issued by Pergamon Press in 1987. In its wake, Pergamon Press has issued seven concise encyclopedias in a variety of applied disciplines (e.g. environmental systems, software engineering, traffic and transportation systems). This eighth concise encyclopedia purports to be a comprehensive
* Concise Encyclopedia of Modelling & Simulation edited by D. P. Atherton and P. Borne. Pergamon Press, Oxford U.K. ISBN 0-08-036201X. £140.00, $280.00.
reference work covering all aspects of modelling and simulation. To this end, it provides approximately 170 alphabetically arranged entries. However, it should be noted that approximately 40% of the entries are relatively terse definitions of key phrases or concepts. The more extended entries emphasize the use of modelling and simulation to assess the behavior of physical processes using mathematical models to the extent practical. Consideration is given to a broad spectrum of systems including aeronautics and space, biological and biomedical, chemical engineering, power plants, ship dynamics, and traffic and transportation. In all cases there is a useful cross-coupling/referencing system, coupled with an extensive subject index, that makes it relatively easy to navigate through the volume. This, in itself, is testimony to the diligence of the encyclopedia's editors, D. P. Atherton and P. Borne. The strengths of this volume are considerable. It draws upon many of the major figures in the field of automatic control for articles that are concise and often elegant. In several cases, key subjects are treated in depth from multiple, reinforcing perspectives. For example, there are 13 entries on the subject of identification, with the contributions of L. Ljung (on the basic problem, least squares method, maximum likelihood method, recursive methods, and time-domain methods) and G. C. Goodwin (on experiment design) being particularly notable. In addition, there are interesting and useful treatments on the nature and use of Petri Nets (by T. Murata and J. P. Bourey et al.), state space modelling (by J. P. Richard and P. Borne, and T. Kailath) and the challenges posed by validating simulation models (by R. G. Sargent). The last area, however, suggests one of the book's shortfalls. There are four entries on the subject of validation (by three contributors) and each contributor defines the term somewhat differently. In many other cases there is a disappointing imprecision in the introduction and consistent use of definitions.
Book Reviews However, it must be noted that for a work that claims to be "a comprehensive reference work covering all aspects of modelling and simulation" there are disconcerting weaknesses and voids. Although there is implicit treatment of a variety of important ancillary subjects (e.g. simulation languages, data dictionaries and repositories, software engineering), their addressal is not commensurate with contemporary interest and activity. For example, there is a wide-spread debate in the modelling and simulation community about the relative strengths and weaknesses of A D A and C + + ; however, little or any insight into the subject could be gleaned from the pages of this volume. The greatest weakness of the volume stems from its failure to address a variety of issues that have become central to research in modelling and simulation. Recently, the U.S. defense community has defined three classes of modelling and simulation: live modelling and simulation, involving instrumented operations with live people and real equipment in the field (e.g. instrumented mock combat at facilities such as the U.S. Army's National Training Center); constructive modelling and simulation, involving the use of classical mathematical models or analytical tools, often implemented on computers; and virtual modelling and simulation, involving systems and personnel in simulators performing simulated functions (e.g. users of aircraft simulators). A vision has been articulated of synthetic environments in which examples of each of these classes would be joined together, seamlessly, and accessible from any point on the globe. Ultimately, such a tool would be used to support a wide variety of activities including operations (e.g. training, the formulation and assessment of alternative concepts of operations) and the acquisition of new systems (e.g. support to technology assessment, prototyping of new concepts). To allow maximum utility and flexibility it is projected that these synthetic environments will be constructed from affordable, reusable components and interoperate through an open systems architecture. The implications of this vision are extraordinary in multiple dimensions. It will require, inter alia, breakthroughs in the technology underlying modelling and simulation (e.g. in the representations of human behavior, including automated forces, and the depicted environment), significant
1623
improvements in supporting systems (e.g. very wide band communications links featuring multicasting; enhanced graphi~ rendering), and innovations in software engineering. Associated with all of these needs is the requirement for an appropriate overreaching architectural vision and associated standards and protocols that the community can employ. Although these issues dominate the interests of a major segment of the modelling and simulation community, they are barely hinted at in the current volume. This suggests that the concise encyclopedia's claim to cover all aspects of modelling and simulation falls considerably short of the mark. In summary, the book in question brings to mind one of the oldest metaphors in literature: the partially filled glass. In this case, it must be said that the liquid that is present has been carefully distilled and is quite nourishing, particularly to the practicing control theorist. However, the contemporary practitioner of modelling and simulation is apt to note the considerable void that is present in the glass and wish for a second edition that slakes that thirst. About the reviwer
Stuart H. Starr received a B.S. in Electrical Engineering from Columbia University, New York, in 1963, and his M.S. and Ph.D. in Electrical Engineering from the University of Illinois, Urbana, Illinois, in 1965 and 1969, respectively. He is Director of Plans, Washington Group, The MITRE Corporation, in McLean, Virginia. His research interests include the development and application of methodologies (with emphasis on the use of modelling and simulation) to plan and assess large, complex systems. Prior to joining MITRE in 1985, he was Assistant Vice President for C3I Systems at M/A-COM Government Systems, Director of Long Range Planning and Systems Evaluation for the Office of the Assistant Secretary of Defense (C3I), and Senior Project Leader at the Institute for Defense Analyses. He is a member of Phi Beta Kappa and Pi Mu Epsilon, a senior member of both the IEEE and AIAA, and a frequent participant in special studies and scientific advisory boards (e.g. consultant to OSD Net Assessment; member of Senior Advisory Group, Office of Technology Assessment).