The paper introduces the concept of "model-free control" and its corresponding "intelligent" PID controllers (iPIDs), which have been successfully applied in various fields. The authors present the basic principles of model-free control, which involve functional analysis and differential algebra. They describe a recent online parameter identification approach that simplifies estimation techniques. The importance of iPIDs, especially in the presence of friction, is highlighted, and the difficulties in tuning classic PID controllers in complex situations are discussed. Several numerical simulations, including infinite-dimensional systems, demonstrate the effectiveness and simplicity of intelligent controllers. The paper also explores the industrial capabilities of classic PIDs and their connection to intelligent controllers, providing a comprehensive overview of the advantages and applications of model-free control.The paper introduces the concept of "model-free control" and its corresponding "intelligent" PID controllers (iPIDs), which have been successfully applied in various fields. The authors present the basic principles of model-free control, which involve functional analysis and differential algebra. They describe a recent online parameter identification approach that simplifies estimation techniques. The importance of iPIDs, especially in the presence of friction, is highlighted, and the difficulties in tuning classic PID controllers in complex situations are discussed. Several numerical simulations, including infinite-dimensional systems, demonstrate the effectiveness and simplicity of intelligent controllers. The paper also explores the industrial capabilities of classic PIDs and their connection to intelligent controllers, providing a comprehensive overview of the advantages and applications of model-free control.