【摘要】 针对传统最优线性二次型控制器中加权矩阵往往由设计者根据经验确定的问题,提出一种应用加速粒子群算法确定加权矩阵的方法。建立"车轮-车身-座椅、人体"6自由度随机振动系统模型,采用加速粒子群算法对座椅悬架进行参数优化,并对优化后系统进行最优线性二次型控制。将基于加速粒子群算法的最优线性二次型座椅悬架系统中"座椅、人体"垂向加速度与初始系统及基于常规粒子群算法和遗传算法的最优线性二次型控制系统进行对比,验证了此控制系统的有效性和优越性。更多还原

【Abstract】 Traditional standard LQR controllers have a disadvantage that the weighting matrices of the controllers need to be determined by the designers according to their experience, which usually makes controllers unable to achieve the global optimum. In this paper, a method of determining the weighting matrices by acceleration based particle swarm optimization(APSO) is proposed. First of all, a six-DOF half-car model including wheel, vehicle’s body, seat and human body is established for random vibration analysis. The parameters of the seat suspension are optimized by APSO, and the LQR optimal control is carried out based on the parameter optimization system. The MATLAB/Simulink is used for the simulation of the parameter optimization system and the LQR control system. The vibration isolation performance of the seat suspension system is indicated by the vertical acceleration of the"seat-human body"system. Results show that the controller based on APSO has better vibration reduction properties than those of the traditional LQR controller based on GA and PSO.更多还原