Model Types In Dynamic Models

Introduction:

One way to analyze a system is to impose disturbances (inputs) on the system and analyze the reaction (outputs) of the system. This is known as“experimental modeling” or model identification.

 

Model Types

 

 A model that is developed by exciting the actual system and measuring its response is called an experimental model. Another way is to analyze the system using an analytical model of the system.

 

 In effect, we represent the system with a model, such as a disturbing a physical system often is less economical or practical than analyzing its analytical model; analytical models are commonly used in practical applications.

Systems for experimental modeling (exciters, measuring devices and analyzers) are commercially available, and experimental modeling is done, if less often than analytical modeling.

In general, models may be grouped into the following categories:

 

1.       Physical models (prototypes)

2.       Analytical models

3.       Computer (numerical) models

4.       Experimental models (using input/output experimental data).

 

Normally, mathematical definitions for a dynamic system are given with reference to an analytical model of the system, for example, a state-space model.

 In that context the system and its analytical model are synonymous. In reality, however, an analytical model, or any model for that manner, is an idealization of the actual system. Analytical properties that are established and results that are derived would be associated with the model rather than the actual system, whereas the excitations are applied to and the output responses are measured from the actual system.

This distinction should be clearly recognized. Analytical models are very useful in predicting the dynamic behavior (response) of a system when it is subjected to a certain excitation (input).

For example, vibration is a dynamic phenomenon and its analysis, practical utilization, and effective control require a good understanding of the vibrating system. A recommended way to control a dynamic system is through the use of a suitable model of the system.

A model may be employed for designing a mechatronic system for proper performance. In the context of product testing, for example, analytical models are commonly used to develop test specifications and the input signal applied to the exciter, and to study dynamic effects and interactions in the test object, the excitation system, and their interfaces. In product qualification by analysis, a suitable analytical model of the product replaces the test specimen.

 In process control, a dynamic model of the actual process may be employed to develop the necessary control schemes. This is known as model-based control.

 

Dynamic Models and Analogies

 

A mechatronic system may consist of several different types of components, and it is termed a mixed system. It is useful then to use analogous procedures for modeling such components. In this manner the component models can be conveniently integrated to obtain the overall model.

 In particular, analytical models may be developed for mechanical, electrical, fluid, and thermal systems in a rather analogous manner, because some clear analogies are present among these four types of systems. In view of the analogy, then, a unified approach may be adopted in the analysis, design, and control of mechatronic systems.