Sampling Time and Improved Kalman Filter-Based Model-Free Adaptive Control: Application to Magnetically Controlled Capsule Systems

This paper addresses the issues of excessive sampling time and noise interference in the magnetic-controlled capsule system by proposing a model-free adaptive control method based on sampling time and an improved Kalman filter. The method introduces a data model that incorporates sampling time along with corresponding parameter update laws to enhance the stability of the control system under long sampling time conditions. Additionally, an improved model-free Kalman filter is integrated into the system, which effectively suppresses interference caused by noise during the magnetic positioning process. Experimental verification demonstrates that the proposed method can effectively mitigate the negative impact of sampling time and significantly improve the system’s noise suppression capability.