Implementing Artificial Intelligence in a RAD Application in the Field of Industrial Automation

In this article, approaches for implementing Artificial Intelligence (AI) functionalities into Rapid Application Development (RAD) environments are explored. The study emphasizes the advantages of building PC-based control systems through RAD applications, considering both speed of development and flexibility. Various strategies for integrating Generative Pretrained Transformers (GPT) models into PC-based industrial control systems are reviewed and proposed. Specific programming implementations in highperformance computing (HPC) languages such as C++ and Python are presented, illustrating practical methods for enabling AI-driven functionalities within industrial environments. A comparative analysis is conducted based on key criteria, including implementation complexity and the execution time for sending and receiving responses from GPT models. Validation is performed through tasks related to technological process control, focusing on PID controller tuning and system identification using example processes. The paper discusses the challenges and benefits of different integration methods and highlights practical guidelines for choosing the most effective approach in real-world applications.