丘陵履带车智能底盘自适应调平控制设计验证OA

To address the problems of attitude instability and operation accuracy degradation caused by decentralized con-trol,lagging hydraulic response and mechanical coupling oscillation in traditional agricultural vehicles chassis during ope-ration on hilly terrain,an integrated adaptive leveling control system for tracked vehicles was innovatively proposed.A four-layer architecture of"perception-decision-execution-adaptation"was built.The perception layer integrated an in-clinometer module to obtain the body posture and slope characteristics in real time.The decision layer adopted a model predictive control(MPC)algorithm to analyze the nonlinear influence of slope on roll angle,based on the chassis-terrain coupled dynamics model,and optimized the leveling trajectory through a multi-objective method.The electro-hydraulic proportional valve control system was designed in the execution layer to achieve four-point synchronous hydraulic leveling.The adaptation layer created a mechanical,hydraulic,electrical architecture at the machine interface to enable quick change.MatLab simulation verification showed that under step slope conditions,the response time of MPC was shortened by 0.3-1.2 s compared with traditional PID,with dynamic leveling accuracy reaching±0.4° and steady-state error not exceeding 0.5°.Furthermore,based on dSPACE hardware-in-the-loop test platform,the robustness of the system under composite slope of 15° and 200 kg step load was verified.The steering deficiency coefficient was reduced by 72.2%and the energy consumption was reduced by 26.6%.In this study,through the coupled dynamics model and the MPC algo-rithm,the traditional control bottleneck was broken through,and its robustness in extreme conditions through hardware was verified,providing theoretical and engineering paradigms for working scenarios such as hilly orchard transport vehicles and bamboo delivery platforms,promoting the development of agricultural machinery chassis in hilly and mountainous areas towards high precision,low energy consumption and strong adaptability.