Direction and Trajectory Tracking Control for Nonholonomic Spherical Robot by Combining Sliding Mode Controller and Model Prediction Controller

Abstract

Spherical robot is a nonlinear, nonholonomic and unstable system which increases the difficulty of the direction and trajectory tracking problem. In this study, we propose a new direction controller HTSMC, an instruction planning controller MPC, and a trajectory tracking framework MHH. The HTSMC is designed by integrating a fast terminal algorithm, a hierarchical method, the motion features of a spherical robot, and its dynamics. In addition, the new direction controller has an excellent control effect with a quick response speed and strong stability. MPC can obtain optimal commands that are then transmitted to the velocity and direction controller. Since the two torque controllers in MHH are all Lyapunovbased sliding mode controllers, the MHH framework may achieve optimal control performance while assuring stability. Finally, the two controllers eliminate the requirement for MPC's stability and dynamic constraints. Finally, hardware experiments demonstrate the efficacy of the HTSMC, MPC, and MHH.

Design and validation of a novel adaptive motion control for a pendulum spherical robot

“…In order to solve the problems of inaccurate dynamic modeling, parameter changes, and interference in the SR control that led to poor performance of traditional controllers, Cai Y. et al [12] proposed a speed control method combining fuzzy logic and SMC, while Kayacan E. et al [13] utilized the adaptive neuro-fuzzy controller and the learning algorithm of the SMC theory for the SR's speed control. Liu Y. et al [14,15] designed a hierarchical SMC (HSMC) for speed and orientation control of the SR, improving control efficiency and stability. Nevertheless, it is challenging to fit sensors in the limited space of the sphere to measure variables such as rolling speed in spherical robots.…”