From the advancement in computers, computer-aided design for mechanical and electronic engineering, architecture and many other engineering fields emerged. Foreseeing a similar development curve and technology wave, we forecast a new emerging discipline in the near future that uses learning-aided approaches for catalysing control development, alongside other similar applications such as in medicine discovery. In this study, we propose a new paradigm of using a machine learning approach to facilitate a quicker, more efficient and effective control development, as a different approach of leveraging the power of machine learning in addition to other options that intent to use learning directly in real-world applications