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Application of Dimensional Analysis in Systems Modeling and by Pedro Balaguer

By Pedro Balaguer

Dimensional research is an engineering instrument that's commonly utilized to various engineering difficulties, yet has just recently been utilized to regulate conception. program of Dimensional research in platforms Modeling and keep watch over layout goals to resolve keep watch over difficulties resembling id and version aid, strong keep an eye on, adaptive regulate and PID control.

This new ebook introduces the basics of dimensional research to either keep watch over engineers and theorists with examples of sensible applicability to commercial keep watch over difficulties. by means of adopting regulate conception learn, the writer describes tips on how to make the most the advantages that dimensional research can provide to regulate theoretic and functional difficulties.

Topics include:
• dimensional research and dimensional similarity
• dynamical structures dimensionless representation
• dimensionless platforms id and version order reduction
• homogeneity of PID tuning rules
• dimensionless PID tuning ideas comparison
• dimensional research regulate fundamentals
• regulate of dimensionally comparable systems
• strong control
• adaptive regulate within the presence of enter saturation
• time scales keep an eye on.

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Extra info for Application of Dimensional Analysis in Systems Modeling and Control Design

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J. S. Bernstein, and R. Venugopal. Dimensional analysis of matrices state-space models and dimensionless units [lecture notes]. Control Systems Magazine, IEEE, 27(6):100–109, 2007 [5] S. Skogestad and I. Postlethwaite. Multivariable Feedback Control. Analysis and Design. Wiley, 1996 [6] T. Szirtes and P. Rózsa. Applied Dimensional Analysis and Modeling. Butterworth-Heinemann, 2007 [7] B. West. ‘The tyranny of many dimensionless constants: a constraint on knowability’. 1 Introduction The dimensionless representation of dynamical systems presented in the previous chapter is the fingerprint for establishing dimensional similarity among dynamical systems.

Workman. Digital Control of Dynamic Systems. Prentice Hall, 1997 M. Zlokarnik. Scale-up in Chemical Engineering. Wiley-VCH, 2002 Chapter 5 Dimensionless systems identification and model order reduction with J. Romero, V. Alfaro and O. 1 Introduction The identification of models from experimental data is the first step in model-based control design. Furthermore, when the model is of high order, it is normal to reduce the model order for a simpler controller design. Low order identified models are the fundamental elements for the design of practical control systems.

33) are equal for the prototype and the model, yielding (ai )m = (ai )p . The equality (bj )m = (bj )p is established by similar reasoning. The discrete time delay is related with the continuous time delay and the sampling time by q = h/Ts . In order to have h (T ) (q)p = (q)m it must follow that hmp = (Tss)mp , which is true by continuous time similarity. Finally, for achieving sampled-data similarity it must also hold the equality in the dimensionless number zSD , that is (zSD )m = (zSD )p .

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