Revised adaptive active disturbance rejection sliding mode control strategy for vertical stability of active hydro-pneumatic suspension

The unmanned ground vehicle (UGV) travels in complex and uncertain terrain. Its vertical stability is a key factor affecting the working state and service life of high-sensitivity on-board sensors and mechanical structures. With the development of unmanned platform, a six-wheel independent drive UGV (6WID UGV) came into being. Its complex operating conditions and the unique configuration of active hydro-pneumatic suspension (AHPS) put forward higher requirements for vertical stability control. Based on the AHPS of 6WID UGV, a revised active disturbance rejection sliding mode controller (R-ADRSMC) is designed to improve the vertical stability of UGV. Firstly, the dynamic model of AHPS was established, and a test platform was built to verify the accuracy of the nonlinear characteristics of stiffness and damping. Secondly, an extended state observer (ESO) is used to estimate the disturbance caused by the model's high nonlinearity and uncertainty. The known disturbance is fed back to ESO to form feedforward compensation, which improves the accuracy of disturbance estimation and compensation. Thirdly, the output of ESO is incorporated into the control law of the sliding mode controller (SMC), giving the control law real-time adaptive capability to the state of suspension system. Finally, the effectiveness of R-ADRSMC and its strong robustness to the uncertainty of road and load parameters are verified by simulation. The results show that compared with passive suspension (PS), active disturbance rejection control (ADRC), and SMC, the proposed R-ADRSMC can effectively improve the vertical stability of UGV under complex road conditions and has better control characteristics.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

Automated summary

An improved active disturbance rejection sliding mode controller (R-ADRSMC) is designed to improve the vertical stability of a six-wheel independent drive unmanned ground vehicle (6WID UGV). The disturbance caused by the model's nonlinearity and uncertainty is estimated using an extended state observer (ESO), and the estimated disturbance is fed back to the controller for feedforward compensation. The effectiveness of R-ADRSMC is verified through simulation, showing that it can effectively improve the UGV's vertical stability under complex road conditions and has better control characteristics compared to other control methods.