This article proposes a novel control method for vehicle active suspension systems in the presence of time-varying input delay and unknown nonlinearities. An unknown system dynamics estimator (USDE), which employs first-order low-pass filter operations and has only one tuning parameter, is constructed to deal with unknown nonlinearities. With this USDE, the widely used function approximators (e.g., neural networks and fuzzy-logic systems) are not needed, and the intermediate variables and observer used in the traditional estimators are not required. This estimator has a reduced computational burden, trivial parameter tuning and guaranteed convergence. Moreover, a predictor-based compensation strategy is developed to handle the time-varying input delay. Finally, we combine the suggested USDE and predictor to design a feedback controller to attenuate the vibrations of vehicle body and retain the required suspension performances. Theoretical analysis is carried out via the Lyapunov–Krasovkii functional to prove the stability of the closed-loop system. Simulation results based on professional vehicle simulation software Carsim are provided to show the efficiency of the proposed control scheme.

中文翻译：

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具有时变延迟的主动车辆悬架控制系统的未知系统动力学估计器


本文提出了一种在存在时变输入延迟和未知非线性的情况下车辆主动悬架系统的新型控制方法。构建了一种未知系统动力学估计器（USDE），它采用一阶低通滤波器运算并且只有一个调整参数，用于处理未知的非线性。通过这种USDE，不需要广泛使用的函数逼近器（例如，神经网络和模糊逻辑系统），并且不需要传统估计器中使用的中间变量和观察器。该估计器减少了计算负担，进行简单的参数调整并保证收敛。此外，还开发了基于预测器的补偿策略来处理时变输入延迟。最后，我们结合建议的 USDE 和预测器来设计反馈控制器，以衰减车身振动并保持所需的悬架性能。通过Lyapunov-Krasovkii泛函进行理论分析，证明闭环系统的稳定性。基于专业车辆仿真软件Carsim的仿真结果显示了所提出控制方案的有效性。