Currently, multiplying a SISOTransferFunction object by a NumPy array results in a dimension error:

importcontrolimportnumpyasnptf=control.TransferFunction([1], [1,0])arr=np.array([    [1,0],    [2,1],])print(tf*arr)print(arr*tf)

ValueError: C = A * B: A has 1 column(s) (input(s)), but B has 2 row(s) (output(s)).

I think it would be convenient if output was a MIMOTransferFunction object of the array's dimension. So, for example,

G=control.TransferFunction(    [        [[1], [0]],        [[2], [1]],    ],    [        [[1,0], [1,0]],        [[1,0], [1,0]],    ],)

I would be happy to implement this and do a PR, but I want to make sure it's something the maintainers actually want. I would think all SISO systems (state-space, etc) should behave in the same way.

This appears to have been discussed in#459 , but I'm not sure what the conclusion was.