Active suspension systems are widely used in vehicles to improve ride comfort and handling performance. However, existing control strategies may be limited by various factors, including insufficient consideration of different operation conditions, such as changing in vehicle mass, defects in strategy design leading to incapability for guaranteeing finite-time stability, lack of considering input effects of dead zone and saturation, excessive energy cost, etc. Importantly, very few results considered the energy-saving performance of active suspension systems although a well-perceived issue in practice. An adaptive fuzzy SMC method based on a bioinspired reference model is established in this article, which is to purposely address these problems and be able to provide finite-time convergence and energy-saving performance simultaneously. The proposed control method effectively utilizes beneficial nonlinear stiffness and nonlinear damping properties that the bioinspired reference model could provide. Therefore, superior vibration suppression performance with less energy consumption and improved ride comfort can all be obtained readily. By using a fuzzy-logic system (FLS), the proposed method is beneficial in compensating for system parameter uncertainties, external disturbances, input dead zones, and saturations. Furthermore, based on the adaptive PD-SMC method, the tracking errors can converge to zeros in finite time. The stability of the equilibrium point of all the states in active suspension systems is theoretically proven by Lyapunov techniques. Finally, simulation results are provided to verify the correctness and effectiveness of the proposed control scheme.

中文翻译：

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输入死区和饱和度的半车主动悬架系统的基于生物动力学的自适应模糊SMC方法

主动悬架系统已广泛用于车辆中，以提高乘坐舒适性和操纵性能。但是，现有的控制策略可能受到各种因素的限制，包括没有充分考虑不同的操作条件，例如车辆质量的变化，策略设计的缺陷导致无法保证有限的时间稳定性，缺少考虑盲区的输入影响以及重要的是，尽管在实践中这是一个容易理解的问题，但很少有结果考虑到主动悬架系统的节能性能。本文建立了一种基于生物启发参考模型的自适应模糊SMC方法，旨在有针对性地解决这些问题，并能够同时提供有限的收敛时间和节能性能。所提出的控制方法有效地利用了生物启发参考模型可以提供的有益的非线性刚度和非线性阻尼特性。因此，可以容易地获得具有更少的能量消耗和改善的乘坐舒适性的优异的减振性能。通过使用模糊逻辑系统（FLS），所提出的方法有利于补偿系统参数的不确定性，外部干扰，输入死区和饱和度。此外，基于自适应PD-SMC方法，跟踪误差可以在有限时间内收敛为零。Lyapunov技术从理论上证明了主动悬架系统中所有状态的平衡点的稳定性。最后，提供仿真结果以验证所提出控制方案的正确性和有效性。