An improved model-free adaptive control with G function fuzzy reasoning regulation design and its applications

This paper proposes an improved model-free adaptive control with G function fuzzy reasoning regulation (MFCF) for general systems where the equations governing the system are unknown. Such an approach has potential advantages in accommodating complex systems with possibly time-varying dynamics and uncertainties. Model-free adaptive control basic algorithm (MFCB) has two features: first, it does not need any mathematical model; second, the control algorithm is simple and is feasible to be applied in actual industry. This paper considers the use of fuzzy reasoning system, which also only requires observed system input—output data. Moreover this improved control algorithm can make use of human experiences. Related to this, a convergence proof of this improved control algorithm is established. The scheme has been used in the control of welding pool dynamics of the arc welding process, and the experiment results validate the control scheme developed. At the same time, this improved controller can enhance control performance.