Abstract
To describe and analyze the subsystems and the overall structure of human–automation systems we need to use appropriate mathematical methods and tools.
The first step in any attempt to study and design a physical system by mathematical methods is to determine a descriptive model of how the system actually works. This process is collectively known as system modeling. Using the mathematical model of a system we can also formulate techniques and develop mathematics-based tools for imitating its operation using a computer. This is known as system simulation. The purpose of this chapter is to provide a brief exposition of the principal mathematical system models and the basic system simulation techniques at a minimal level of detail which assures their understanding and interpretation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
W.R. Ashby, An Introduction to Cybernetics (Wiley, New York, 1975)
K.L. Boettcher, A.H. Levis, Modeling the interacting decision maker with bounded rationality. IEEE Trans. System Man Cybernet. SMC-12(3), 334–344 (1982)
G.R. Cooper, C.D. McGillem, Probabilistic Methods of Signal and System Analysis (Holt, Rinehart and Winston, New York, 1971)
R.C. Dorf, R.H. Bishop, Modern Control Systems (Prentice Hall, Upper Saddle River, NJ, 2001)
J. Harris, An Introduction to Fuzzy Logic Applications (Kluwer, Boston, 2000)
J. Harris, Fuzzy Logic Applications in Engineering Science (Springer, Dordrecht, 2006)
M.M. Meerschaert, Mathematical Modeling (Academic, San Diego, 1999)
K. Ogata, Modern Control Engineering (Prentice Hall, Upper Saddle River, NJ, 1997)
A. Papoulis, Probability, Random Variables and Stochastic Processes (McGraw-Hill, New York, 1991)
A.M. Polovko, Fundamentals of Reliability Theory (Academic, San Diego, 1968)
T.B. Sheridan, W. Ferrell, Man–Machine Systems: Information, Control and Decision Models of Human Performance (MIT Press, Cambridge, MA, 1974)
S.G. Tzafestas, Optimization of system reliability: A survey of problems and techniques. Int. J. Syst. Sci. 11(11), 455–486 (1980)
S.G. Tzafestas, A.N. Venetsanopoulos, Fuzzy Reasoning in Information, Decision and Control Systems (Kluwer, Dordrecht/Boston, 1994)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Tzafestas, S.G. (2010). Mathematical Tools for Automation Systems I: Modeling and Simulation. In: Human and Nature Minding Automation. Intelligent Systems, Control and Automation: Science and Engineering, vol 41. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3562-2_11
Download citation
DOI: https://doi.org/10.1007/978-90-481-3562-2_11
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-3561-5
Online ISBN: 978-90-481-3562-2
eBook Packages: EngineeringEngineering (R0)