How to efficiently and effectively integrate feedback information in controlling and regulating dynamical systems is an important yet very challenging and complex task. The complexity stems not only from the complexity of dynamical systems [11, 17] but also from the quality and accuracy of the feedback information. Given its well-known performance in enabling and regulating dynamical systems to track reference signals, we plan to explore the use of the modified internal model control approach, where the basics were also presented in the previous chapter. While the internal model control approach [5–8, 21, 22] can be used both in training and the implementation of neural networks [3, 13, 19, 20, 24], we will concentrate on the implementation part, but in a nonstandard way as it will be shown. In line of this, we will assume that the recurrent neural network is of generic type, and has already been trained, without getting into too much specific details on how it has been trained. Some dynamical properties of the long short-term memory and gated recurrent unit neural networks have been discussed in previous chapters of this book, yet the presentation in this chapter will be kept independent and applicable to general recurrent neural networks. Furthermore, by formulating our approach in a specific way we will be able to bypass dynamical intricacies and complexities that some specific recurrent neural networks like long short-term memory neural networks impose yet still be able to integrate them into our formulation. This specific formulation and integration will be based on our motivation to use modified internal model control approach to enhance classification capabilities of a given recurrent neural network to be regulated to track and recognize input reference signals. As mentioned in the previous chapter, the main motivation for the tracking specification and formulation with recurrent neural networks is that the problem of tracking an unknown reference signal is essentially related to recognizing or classifying that time-varying or time-invariant reference input signal.