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Simulating the levitation system

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The levitation system

The magnetic levitation system is one of the Mechanics systems that is widely appreciated and accepted by the people worldwide due to the fact that it’s environmentally friendly and reduces the transportation cost. Magnetic levitation systems may sound like a newly conceived idea that emerged in the 1970s or later. However, this idea has been there for about a century. Transrapid International is the company that has implemented the idea of a levitation system. The Levitation system’s first application was in 2004, Shanghai, China.

How the system works.

To better understand how the system works, we shall use the analogy of a maglev train, which is its real application. The system uses the idea of repulsion and attraction in magnets. Repulsion is used to suspend the train in the air while attraction is used to propel the train forward. The result is that we have a frictionless train that uses minimal energy and does not produce a lot of sounds. Such trains do not have wheels or engines.

To simulate the system, we must have a model. A model is defined as a mathematical representation of the system. Most models are produced using mathematical equations. One of the ways, in which we can develop, the maglev model, is through the nonlinear autoregressive with external input neural network. The model predicts the dynamic behavior of the levitation system. Neural network models are always preferred as they produce more accurate results with time-series data.

The general steps in the simulation exercise

Once the model is identified, the following general steps are always followed in the simulation process.

  1. Problem definition. What are you trying to achieve? What is the goal?
  2. Model formulation.
  3. Model testing. It involves comparing the model with the actual behavior of the actual problem
  4. Collect and identify the data necessary in the simulation.
  5. Run the simulation.
  6. Analyze the results of the simulation exercise.

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