基于混合遗传算法的主动悬架集成优化研究

作者提出的主动悬架的集成优化方法是以主动悬架的结构参数与LQG控制器为优化对象，以主动悬架系统输出的车身垂直加速度、悬架动位移、轮胎动位移和主动控制力的加权和为优化性能指标。同时提出了一种混合优化算法，它利用梯度算法每次迭代得到的结果来改进遗传算法的群体，而用遗传算法的最优个体与梯度算法的迭代解相比较，选择其中的最优点作为梯度算法下一步迭代的初始点。运用该混合遗传算法进行主动悬架系统的集成优化控制能有效地提高汽车行驶平顺性和安全性。

Integrated Optimization for Active Suspension Using Hybrid Genetic Algorithm

An integrated optimization method for active suspension is presented in this paper, which takes the structure parameters of active suspension and LQG controller as optimization object and takes the weighted sum of the vertical acceleration of body, the dynamic displacements of suspension and tyre and the active control force as optimization performance indicators. At the same time, a hybrid genetic algorithm is proposed to optimize active suspension, which uses the results of gradient algorithm to improve the populations of genetic algorithm, and selects the optimum point as the start point of next iteration of gradient algorithm by comparing the best point of genetic algorithm with the last result of gradient algorithm. The results of simulation show that the method can effectively enhance the ride performance and safety of the vehicle.