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A smooth is a first-order exponential information delay. It is typically used to model time lags in forming an expectation or in perceiving some information.

Inside the converter there actually is a stock x that stores the perceived or expected value of the information input u. The output y is derived immediately from x as can be seen from these equations where τ denotes the delayTime:

Notes

• The delayTime given (either as constant parameter or continuous signal) will be clipped to a minimum value of modelSettings.dt, which denotes the smallest possible process time anywhere in the model. The time of delay for the process of information perception or expectation formation can thus never be zero or negative.

• In the system dynamics community a smooth is an information delay (as opposed to a material delay) [1, Appendices E and H]. Information delays model the process of updating information to the actual value. Since the technical procedure is called exponential smoothing, the name smooth has prevailed.


• The parameter init in the Advanced tab allows to select →InitializationOptions:
  
  • FixedValue (default) will use the parameter initialValue to determine the initial output y.
  
  
  • SteadyState will set the initial output y equal to the initial input u.
  
  
  • Free there will be no initial equation and thus the solver is free to find an initial output using initialValue as an initial guess.

See also

SmoothN, AsymmetricSmooth, Decay