Height Adaptive LQR Control of a Two-Wheel Legged Robot via Closed-Loop Frequency Identification

Abstract

This paper proposes a height adaptive Linear Quadratic Regulator (LQR) control framework for a two-wheel legged robot, using closed-loop frequency domain identification to enhance stability and adaptability across varying robot heights. Conventional LQR control strategies often employ a linearized model obtained from a single operating condition, such as a fixed height. While these strategies can maintain stability when height changes are small, they struggle to maintain optimal performance under significant height variations due to either the robot's own adjustments or additional loads, which are common for two-wheel legged robots. To address this challenge, we propose a novel approach that integrates closed-loop frequency identification with an adaptive LQR controller. The frequency identification module identifies the system's closed-loop natural frequency, enabling the identification of the robot system's height. This information allows the LQR controller to adjust its parameters for optimized performance. Experimental results demonstrate that the proposed method significantly improves the robot's stability and robustness during height transitions, outperforming conventional fixed-parameter LQR controllers.