Artificial intelligence (AI) is reshaping engineering education by offering adaptive, interactive, and data-driven learning environments. This paper examines the primary roles of AI in enhancing control engineering education (CEE), with emphasis on sensing-oriented applications such as sensor-based system modelling, AI-assisted signal processing, and data-driven state estimation-domains that underpin modern sensing, communication, and control systems. The paper discusses how AI tools, particularly MATLAB and Simulink integrated with machine learning and reinforcement learning capabilities, can serve as effective pedagogical instruments for teaching complex topics including nonlinear contro... More >

This paper focuses on the implementation of a control framework for a fixed wing aircraft system and the simulation demonstrations. The aim is to develop several Proportional Integral Derivative (PID) controllers to stabilise the altitude and attitude in a 2D environment by regulating the engine power, the pitch angle, and height in flight operation. In technique, a dynamic mathematical model is established by considering the degrees of freedom and the dynamics of motion of a fixed wing aircraft, which provide a foundation for design and simulation. A simplified aircraft dynamic model is tailored for testing the formed control systems, which can be flexibly modified with different aircraft c... More >

This study explains the main idea and structure of an integrated What-How intelligent control and universal control (I-U-control) system. The proposed framework consists of two control layers. The bottom layer uses the U-control framework to manage 'How' to control within a universal framework. The top layer uses intelligent control (I-control) to coordinate and guide 'What' to achieve both global and local control goals. This study also reviews the configurations, functions, and integration of these two control layers in analysis, design, and applications. More >