When developing an entire vehicle system, testing the structure of the vehicle or each component as a module or individually is necessary to determine the reliability and ensure the endurance of the entire vehicle. Various tests have been conducted to check the durability of the parts. However, the most important part is the verification of the fatigue limit of the load vibration from the road surface when the vehicle is being driven. Verification can be achieved by experimenting while driving on a real road with a prototype vehicle best suited to the actual conditions. However, issues such as problems in time, space, and environmental constraints, inconsistency in driving characteristics of the test driver, and continuous monitoring exist. For testing the load vibration of the road surface in automobile parts in the laboratory, hydraulic servo actuators are used because they provide vibrational loads in multiple directions by configuring them in multiple axes rather than a single axis. In this article, a multiple-input multiple-output model predictive control–proportional–integral–derivative hybrid controller is proposed as the method for optimal control of a multi-axis hydraulic servo actuator used in a random road signal reproduction experiment. Its performance is compared with the simple proportional–integral–derivative controller. A method for obtaining an efficient black box multiple-input multiple-output system model using LabVIEW in a laboratory in the field is also introduced, and the effectiveness of the model predictive control–proportional–integral–derivative hybrid controller is shown by reproducing the actual road load.

在开发整个车辆系统时，需要测试车辆的结构或将每个组件作为模块或单独进行测试，以确定可靠性并确保整个车辆的耐久性。已经进行了各种测试以检查零件的耐用性。然而，最重要的部分是验证车辆行驶时来自路面的负载振动的疲劳极限。可以通过在真实道路上驾驶最适合实际条件的原型车进行实验来实现验证。但是，存在诸如时间，空间和环境限制的问题，测试驾驶员的驾驶特性不一致以及连续监视之类的问题。为了在实验室中测试汽车零件的路面载荷振动，之所以使用液压伺服执行器，是因为它们通过将其配置为多个轴而不是单个轴来提供多个方向的振动负载。在本文中，提出了一种多输入多输出模型预测控制-比例-积分-微分混合控制器，作为在随机道路信号再现实验中使用的多轴液压伺服执行器的最优控制方法。将其性能与简单的比例积分微分控制器进行比较。还介绍了一种在实验室中使用LabVIEW获取有效的黑匣子多输入多输出系统模型的方法，并通过重现实际值来展示模型预测控制-比例-积分-微分混合控制器的有效性。道路负荷。