Applied Sciences (Jul 2023)
Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
Abstract
Trajectory tracking is a crucial aspect of controlling nonlinear systems and is an important area of research. Researchers have proposed several strategies to perform this task in the presence of perturbations, which are the sum of a system’s uncertainty, modeling errors, and external disturbances. Nonlinear systems, such as robot manipulators, have complex dynamics, and deriving their exact mathematical models is a tedious task. Therefore, the objective of this research is to design a model-free form of control for such systems. To achieve this goal, a sliding mode control (SMC) with a proportional-integral-derivative (PID) sliding surface was designed and integrated with a saturation-function-based extended-state observer (ESO). In an extended-state observer (ESO), the primary concept is to define the system’s perturbation. The ESO estimates the system’s states and perturbation, including the known and unknown dynamics, uncertainties, and external disturbances, which are considered as perturbations. The estimated perturbation is used in a closed loop to cancel the actual perturbation. This perturbation-rejection technique improved the controller’s performance, resulting in reduced position error, reduced sensitivity to low-frequency elements of perturbation, and a small magnitude of switching gain. The designed control algorithm requires minimal information about the system, specifically position feedback, and, therefore, there is no need to identify the system parameters. A mathematical analysis of the designed algorithm was performed in detail, and the algorithm was compared with the existing ESO-based SMC algorithm. Simulations were conducted using MATLAB/SimMechanics on two different systems, and the comparison results validated the performance of the designed algorithm in comparison to previous research.
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