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This article is about what simulink is in Matlab. Xiaobian thinks it is quite practical, so share it with everyone for reference. Let's follow Xiaobian and have a look.

Basic knowledge of simulink

Simulink is an important part of matlab software, which can carry out system modeling, simulation and comprehensive analysis, and provides an interactive graphical environment. In simulink, every system in reality can be regarded as a mathematical function relationship composed of three basic elements: input, output and state, which changes with time. It is more and more widely used in academic and industrial fields.

Simulink is a visual simulation tool in matlab. It is a software package to realize dynamic system modeling, simulation and analysis. It is widely used in linear system, nonlinear system, digital control and familiar signal processing. simulink can be modeled with continuous sampling times, discrete sampling times, or a mixture of both. It also supports multi-rate systems, i.e. different parts of the system have different sampling rates. In order to create dynamic system models, simulink provides a graphical user interface (GUI) for building model block diagrams, which can be done with just click and drag mouse operations. It provides a faster and more straightforward way for users to see the simulation results of the system immediately.

Simulink provides an integrated environment for dynamic system modeling, simulation, and comprehensive analysis, where complex systems can be constructed with simple and intuitive mouse operations without extensive programming.

Simulink has the advantages of wide adaptability, clear structure and flow, fine simulation, close to reality, high efficiency and flexibility. Based on these advantages, simulink has been widely used in complex simulation and design of control theory and digital signal processing. There is also a large number of third-party software and hardware available for use with simulink.

The process of modeling with simulink can be simply understood as selecting the required modules from the modeling library, then condensing and setting the attributes of these modules, finally running the system, and viewing the simulation results.

Subsystem and its packaging

As models become larger and more complex, there are so many modules that it is difficult for users to easily understand the model. Therefore, the large model can be divided into some small subsystems, each subsystem can adopt modular design method, the hierarchy is very clear, some commonly used modules are integrated together, and reuse can be realized.

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