基于粒子群算法的主动悬架模型预测控制研究

Research on Model Predictive Control of Active Suspension Based on Particle Swarm Algorithm

摘要: 针对汽车主动悬架系统在复杂路况下的多目标协同优化问题，本文提出了一种基于粒子群优化算法(Particle Swarm Optimization, PSO)的模型预测控制(Model Predictive Control, MPC)策略。首先，通过创建四分之一车辆主动悬架系统的动力学模型，以车身垂直加速度为主要控制目标，同时统筹悬架动行程、轮胎动位移及执行器约束；其次，设计PSO-MPC控制器，通过PSO算法全局优化MPC的权重矩阵，克服传统MPC参数依赖人工调节的局限性；最后，对比分析线性二次调节器(Linear Quadratic Regulator, LQR)、传统MPC、PSO-MPC及被动悬架的性能指标。仿真结果表明，相比被动悬架系统，在随机路面和凸块路面激励下，PSO-MPC使车身垂直加速度的均方根(Root Mean Square, RMS)值分别降低了49.99%和72.22%，悬架动行程的RMS值分别减少24.23%和32.86%，轮胎动位移的RMS值分别下降32.49%和69.53%。这些结果验证了所提出的控制方法在同时提升车辆行驶安全性、乘坐舒适性及操纵稳定性方面的综合优势。

Abstract: To address the multi-objective collaborative optimization problem of automotive active suspension systems under complex road conditions, this paper proposes a model predictive control (MPC) strategy based on the particle swarm optimization (PSO) algorithm. First, a dynamic model of the quarter vehicle active suspension system is created, with body vertical acceleration as the primary control objective, while simultaneously considering suspension dynamic travel, tire dynamic displacement, and actuator constraints; Second, a PSO-MPC controller is designed, where the PSO algorithm globally optimizes the weight matrix of the MPC, overcoming the limitation of traditional MPC where parameters rely on manual adjustment; finally, the performance metrics of the linear quadratic regulator (LQR), traditional MPC, PSO-MPC, and passive suspension systems are compared and analyzed. Simulation results show that compared to the passive suspension system, under random road surface and bumpy road surface excitations, the PSO-MPC reduces the root mean square (RMS) value of body vertical acceleration decreased by 49.99% and 72.22%, respectively, the RMS value of suspension dynamic travel by 24.23% and 32.86%, respectively, and the RMS values of tire dynamic displacement decreased by 32.49% and 69.53%, respectively. These results validate the comprehensive advantages of the proposed control method in simultaneously enhancing vehicle driving safety, ride comfort, and maneuvering stability.