Disturbance-Aware Sliding Mode Control for Automated Optical Tweezers Using Nonlinear Observation

Abstract

This paper presents a control-oriented framework for automated optical tweezers (AOT), explicitly accounting for fluid dynamics and common real-world disturbances. AOT operation is strongly affected by unmeasurable flow-induced forces and stochastic perturbations under noisy vision feedback, which poses additional challenges for disturbance estimation and robust control design. To estimate unmeasurable perturbations and suppress visual observation noise, an extended nonlinear high-gain observer (NHGO) is developed to reconstruct dominant low-frequency disturbances, while a super-twisting sliding mode controller (STSMC) is employed to attenuate residual high-frequency perturbations and achieve chatter-reduced robust tracking. The observer and controller are jointly designed according to the disturbance characteristics of AOT systems. Simulation and experimental results in two representative AOT scenarios demonstrate substantial improvements in tracking accuracy, robustness, and disturbance rejection compared with conventional and SMC-based baseline methods.