Why my regression model always be dominanted by one feature?
The first thing that comes to my mind is that you might have not normalized your features correctly. Generally a feature ranging between a bigger range of values, compared to the other ones, is going to be more influencial in terms of the models' output.
In order to midigate this issue, one common practise is to transform your features into having zero-mean and a variance of one. In this way, it is guaranteed that all your features have identical range of values.
Other than that, It may be just that the dominant feature is indeed more indicative for your time series prediction and thus your model has learned to rely its predictions on this specific feature.