Path Tracking Control of Magnetic Helical Swimmer Under Fluid Flow Condition

To ensure the safety and effectiveness of in vivo therapy using magnetic helical swimmers, achieving precise path tracking performance is crucial. However, controlling the 3D path tracking of helical swimmers in fluid flow conditions presents significant challenges due to nonlinear dynamic interactions and input saturation. In this context, a robust 3D path tracking control framework is proposed, combining a disturbance observer with an adaptive finite-time sliding mode controller to autonomously guide the helical swimmer along desired paths. First, a kinematic model for the helical swimmer is established based on a 3D hand position approach. Next, a robust smooth differentiator is implemented as an observer to estimate disturbances within a finite time frame. Following this, an adaptive finite-time sliding mode controller is investigated to ensure accurate 3D path tracking. This controller’s adaptive mechanism guarantees rapid system convergence while mitigating chattering. Finally, a rigorous theoretical analysis of the finite-time stability of the entire closed-loop system is provided using Lyapunov functions. Experimental results demonstrate that the proposed framework surpasses existing methods in terms of control accuracy and convergence time, thereby validating its effectiveness.