Robots are increasingly tasked with performing complex tasks that involve moving and collaborating, both with other robots and humans. A recent paper published in IEEE/CAA Journal of Automatica Sinica (JAS) highlights a new approach to controlling the tracking of self-balancing mobile robots.
Traditionally, the movement of most robots is regulated by a technique known as sliding mode control. This pulls in information from the nonlinear system, which can then behave differently depending on a range of factors. This information is then organized into a clear representation of the normal behavior of the robot.
"Although different [sliding mode control] schemes have been extensively studied in the practical systems, it needs to be further developed for the self-balancing robot," the author says.
The author also believes that the dynamic information contained within a variable, known as the unknown disturbance, should be more effectively utilized. In order to better understand this unknown disturbance, a disturbance observer was introduced into the sliding mode control method. This helps to determine the value of this disturbance and to, therefore, allow the sliding-control method to adjust sufficiently that the robot can continue to function normally.
The author believes more work is still required, however, and proposes a modified version to provide better performance.
"By using the output of the nonlinear disturbance observer, the tracking control scheme has been designed using the sliding mode technique to guarantee that all the closed-loop signals are ultimately uniformly bounded," they say. "The robot, no matter the disturbance, should still end up moving in the desired trajectory."
The algorithm was tested out on a self-balancing mobile robot at the Googol Technology Consulting, Inc. company. The Chinese tech company specializes in the development of controller-based systems.
"The simulation results have shown that a good tracking performance has been achieved," the author says. "In future work, the experimental study will be done for the self-balancing mobile robot."