For the same actual system, people can build different models for different purposes and purposes. But any model built is just a simplification of the actual system prototype, because it is neither possible nor necessary to enumerate all the details of the actual system.
Introduction Modeling is about building models: modeling: the process of building a system model. Also known as modeling. Modeling is an important means and prerequisite for researching systems. Any process that uses a model to describe the causal or interrelationship of a system is modeled. The relationships depicted in the diagram vary, so the means and methods for achieving this process are diverse. It can be modeled according to the mechanism of motion of the system itself, or by the processing of experimental or statistical data of the system, and according to the existing knowledge and experience of the system. You can also use several methods at the same time.
System system modeling is mainly used in three aspects.
1 Analyze and design the actual system. For example, when the engineering community analyzes and designs a new system, it usually performs mathematical simulation and physical simulation experiments, and finally goes to the site for physical experiments. Mathematical simulation is simpler and easier than physical simulation. When using mathematical simulation to analyze and design an actual system, there must be a model that describes the characteristics of the system. For many complex industrial control processes, modeling is often the most critical and difficult task. Qualitative or quantitative research on social and economic systems also begins with modeling. For example, in population control theory, establishing various types of population models and changing some parameters in the model can analyze the impact of population policies on population development.
2 predict or forecast future trends in certain states of the actual system. Forecasting or forecasting is based on the coherence of the process of development of things. For example, a mathematical model of meteorological changes is established based on past measurement data for forecasting future weather.
3 implement optimal control of the system. The key or premise for designing a controller or optimal control law using control theory is to have a mathematical model that characterizes the system. On the basis of modeling, various controllers or control laws are designed according to the methods of maximum value, dynamic programming, feedback, decoupling, pole placement, self-organization, self-adaptation and intelligent control.
For the same actual system, people can build different models for different purposes and purposes. But any model built is just a simplification of the actual system prototype, because it is neither possible nor necessary to enumerate all the details of the actual system. If some essential features of the system prototype can be preserved in the simplified model, then the model can be considered similar to the system prototype and can be used to describe the original system. Therefore, in actual modeling, an appropriate compromise must be made between the simplification of the model and the accuracy of the analytical results, which is often a principle followed by modeling.
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