An MPC-based Optimal Motion Control Framework for Pendulum-driven Spherical Robots

TL;DR

This paper introduces an MPC-based motion control framework for spherical robots that improves tracking accuracy, attitude stability, and energy efficiency compared to traditional control methods, verified through physical experiments.

Contribution

The paper develops a novel MPC-based control framework with dual controllers, integrating ESO-MPC and MLP-assisted MPC, tailored for spherical robot motion control.

Findings

Outperforms PID in rapidity and accuracy

Reduces overshoot and improves attitude stability

Enhances current stability and reduces energy consumption

Abstract

Motion control is essential for all autonomous mobile robots, and even more so for spherical robots. Due to the uniqueness of the spherical robot, its motion control must not only ensure accurate tracking of the target commands, but also minimize fluctuations in the robot's attitude and motors' current while tracking. In this paper, model predictive control (MPC) is applied to the control of spherical robots and an MPC-based motion control framework is designed. There are two controllers in the framework, an optimal velocity controller ESO-MPC which combines extend states observers (ESO) and MPC, and an optimal orientation controller that uses multilayer perceptron (MLP) to generate accurate trajectories and MPC with changing weights to achieve optimal control. Finally, the performance of individual controllers and the whole control framework are verified by physical experiments. The experimental results show that the MPC-based motion control framework proposed in this work is much better than PID in terms of rapidity and accuracy, and has great advantages over sliding mode controller (SMC) for overshoot, attitude stability, current stability and energy consumption.