This paper presents an improved version and a modification of Robust Evolving Cloud-based Controller (RECCo). The first modification is normalization of data space in RECCo. As a consequence, some of the evolving and adaptation parameters become independent of the range of the process output signal. Thus the controller tuning is simplified which makes the approach more appealing for the use in practical applications. The data space normalization is general and is used with Euclidean norm, but other distance metrics could also be used. Beside the normalization
new adaptation scheme of the controller gain is proposed which improves the control performance in the case of a negative initial error in starting phase of the evolving process. At the end, different simulation scenarios are tested and analyzed for further practical implementation of the
Cloud-based controller into real environments. For that reason a detail simulation study of a plate heat exchanger is performed and different scenarios were analyzed.