This paper introduces a multiple-input discrete Urysohn operator for modelling nonlinear control systems and a technique of its identification by processing the observed input and output signals. It is shown that the identification problem always has an infinity of solutions, which exactly convert the inputs to the output. The suggested iterative identification procedure, however, leads to a unique solution with the minimum norm, requires only few arithmetic operations with the parameter values and is applicable to a real-time identification, running concurrently with the data reading. It is also shown that, depending on the input signal ranges, the discrete Urysohn operator can be identified partially and used in such form, which makes this dynamic model uniquely different to many others. The efficiency of the proposed modelling and identification approaches is demonstrated using an example of a non-linear mechanical system, which is represented by a differential equation, and an example of a complex real-world dynamic object.