Basically, a Dynamic models  involves some thing like lagged variables.

e.g: Y(t)-Y(t-1)=b[Y'(t)-Y(t-1)]+v(t), v(t) is the error term at time t and it's i.i.d and E(v)=0.

The Equation above illustrates that, the changes in the value of Y from the t-1 time point to the time point of t is propertional to the difference between any gap which has opened up between the target value, Y'(t), and the opening period value Y(t-1).

The closer b is to 1, the quicker is this adjustment.

I could remind you that, Dynamic Models always deal with the changes in the value of a certain variable. If you keep this meaning in your mind, it would be easy to understande the Dynamic Models. However, the example given above is the simplest case, which called the Dynamic Bivariate Models, if you are very interested in this kind of time series analysis, you'd better to have an extending reading, namely, the Dynamic Multivariate Models, something like the Vector Autoregression Model, or VAR for short.

Ok, good luck and happy new year~