基于智能体理论的空气悬架阻尼最优控制研究

Research on Optimal Damping Control of Air Suspension Based on Agent Theory

为改善空气悬架的乘坐舒适性、行驶平顺性,基于BDI智能体理论建立了阻尼控制智能体系统。该系统由信念模块、愿望模块、意图模块组成。信念模块通过传感器从环境获取悬架状态信息。内置遗传算法,该算法能帮助智能体不断完善评价权重q1,q2,q3,并根据完善结果,调整适应当前工况的评价权重,使得阻尼控制智能体系统获得最优控制力输出。愿望模块包括愿望产生器和愿望库,愿望库存储愿望,即评价指标最小这一愿望;意图模块包括意图产生器和意图库,意图库存储达到愿望的方案。系统在5种工况下进行仿真,验证所搭建模型的准确性及控制效果。结果表明,与传统空气悬架相比,阻尼控制智能体能有效改善行驶平顺性、乘坐舒适性。

In order to improve ride comfort and smooth running of air suspension,a damping control agent system is established based on BDI agent theory.The system consists of belief module,desire module and intention module.The belief module obtains suspension status information from the environment through sensors.The built-in genetic algorithm can help the agent to continuously improve the evaluation weights q1,q2 and q3,and adjust the evaluation weight to adapt to the current working conditions according to the improvement results,so that the damping control agent system can obtain the optimal control force output.The desire module includes the desire generator and the desire inventory,and the desire inventory stores the desire,that is,the desire with the least evaluation index;the intention module includes the intention generator and the intention database,and the intention inventory stores the plan of the desire.The system is simulated under five working conditions to verify the accuracy and control effect of the model.The results show that,compared with the traditional air suspension,the damping control agent can effectively improve smooth running and ride comfort.