基于路面识别的电磁混合式悬架自适应模糊控制

Adaptive fuzzy control of an electromagnetic hybrid suspension based on road recognition

为改善不同路面等级上主动悬架动态性能与馈能特性适应性差的问题,设计了一种基于路面等级识别的电磁混合式悬架自适应模糊控制。采用天牛须搜索(beetle antennae search, BAS)算法优化了神经网络权值阈值,建立了BAS-BP(beetle antennae search-back propagation)路面识别模型;设计了自适应模糊PID(proportional integral derivative)控制器,针对不同路面等级设计了三种目标函数并引入了主动力反馈调整论域;仿真分析了悬架动态性能与馈能特性,并进行了台架试验。仿真结果表明,相比于模糊PID控制,自适应模糊控制的悬架系统在A级、B级路面簧载质量加速度均方根值分别降低了13.28%、13.84%,在B级、C级、D级路面轮胎动载荷均方根值分别降低了9.09%、16.07%、15.54%,并实现了42.8 W的振动能量回收。试验结果表明,与仿真分析相比,各路面等级上时域、频域的相对误差均在16%以内,验证了仿真结果的正确性和系统的实用性。

In order to improve the poor adaptability of the dynamic performances and energy regenerative characteristics of an active suspension on different road levels,the adaptive fuzzy control of an electromagnetic hybrid suspension based on road level recognition was designed.The beetle antennae search-back propagation(BAS-BP)road recognition model was established by optimizing the neural network weight threshold with the BAS algorithm.An adaptive fuzzy proportional integral derivative(PID)controller was designed.Three objective functions were designed for different pavement levels and the main dynamic feedback theoretical adjustment domain was introduced.The dynamic performances and energy regenerative characteristics of the suspension were analyzed by simulation and a bench test was carried out.The simulation results show that:compared with the fuzzy PID control,the root mean square of sprung mass acceleration of the suspension system with the adaptive fuzzy control is reduced by 13.28%and 13.84%on grade A and B road surface respectively,the root mean square of dynamic load on the tire on grade B,C and D road surface is reduced by 9.09%,16.07%and 15.54%respectively,and 42.8 W vibration energy recovery is achieved.The experimental results show that,compared with the simulation analysis,the relative errors in time domain and frequency domain are within 16%,which verifies the correctness of the simulation results and the practicability of the system.