Novel Adaptive Sliding Mode Control with Nonlinear Disturbance Observer for SMT Assembly Machine

Abstract

This paper presents a novel adaptive sliding mode control based on nonlinear sliding surface with disturbance observer (ANSMC-DOB) for precision trajectory tracking control of a surface mount technology (SMT) assembly machine. A two-degree-of-freedom model with time-varying parameter uncertainties and disturbances is built to describe the first axial mode of the pick-place actuation axis of the machine. According to the principle of variable damping ratio coefficient which makes the system have a nonovershoot transient response and a short settling time in the second-order system, the nonlinear sliding surface is designed for the sliding mode control (SMC). Since the upper bound value of the disturbances is unknown, the adaptive gain estimation is applied to replace the switching gain in the SMC. In order to settle the problem of SMC unrobust to the mismatched parameter uncertainties and disturbances, the nonlinear disturbance observer is introduced to estimate the mismatched disturbances and form the novel controller of ANSMC-DOB. The stability of sliding surfaces and control laws are verified by the Lyapunov functions. The simulation research and comparative experiments are conducted to verify the improvement of positioning accuracy and robustness by the proposed ANSMC-DOB in the SMT assembly machine.

Robust sliding model control-based adaptive tracker for a class of nonlinear systems with input nonlinearities and uncertainties

“…Moreover, the paper (Mondal and Mahanta, 2013) mentioned that the adaptive law should avoid overestimation. In Qian et al (2016), by using threshold value, a method was proposed for preventing the adaptive gain from high gain property. Therefore, to avoid high gain problem for the robust tracker design, we will introduce and extend the concept proposed in the literature.…”

Design of Robust Trackers and Unknown Nonlinear Perturbation Estimators for a Class of Nonlinear Systems: HTRDNA Algorithm for Tracker Optimization

“…Suppressing disturbance is the main target of SMC, but it cannot eliminate disturbance completely. Some researches utilize the disturbance estimators to overcome external disturbance [20,21]; the papers develop SMC to integrate with the disturbance estimator for the controlled system with undesired disturbance [22][23][24][25]. The authors of [25] propose the observer-based SMC for the controlled system with external disturbances.…”