The results presented in this chapter demonstrate, for the first time, that incorporating nonlinearity into active vibration control can substantially reduce energy consumption compared with existing active control strategies. A bioinspired dynamics‑based adaptive tracking control approach is developed for nonlinear suspension systems. Conventional methods typically expend considerable control effort to counteract vibration energy introduced by inherent suspension nonlinearities in order to enhance ride comfort. In contrast, the proposed method exploits beneficial nonlinear stiffness and damping characteristics inspired by the limb motion dynamics of biological systems, enabling favorable nonlinear suspension behavior with potentially lower energy requirements. The stability of the desired bioinspired nonlinear dynamics is rigorously analyzed using the Lyapunov framework. Both theoretical analysis and simulation results confirm that the proposed bioinspired nonlinear dynamics‑based adaptive controller achieves comparable ride comfort performance under random road excitations while significantly reducing energy consumption.

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X-Dynamics-Based Adaptive Tracking Control for Nonlinear Suspension Systems

  • Xingjian Jing

摘要

The results presented in this chapter demonstrate, for the first time, that incorporating nonlinearity into active vibration control can substantially reduce energy consumption compared with existing active control strategies. A bioinspired dynamics‑based adaptive tracking control approach is developed for nonlinear suspension systems. Conventional methods typically expend considerable control effort to counteract vibration energy introduced by inherent suspension nonlinearities in order to enhance ride comfort. In contrast, the proposed method exploits beneficial nonlinear stiffness and damping characteristics inspired by the limb motion dynamics of biological systems, enabling favorable nonlinear suspension behavior with potentially lower energy requirements. The stability of the desired bioinspired nonlinear dynamics is rigorously analyzed using the Lyapunov framework. Both theoretical analysis and simulation results confirm that the proposed bioinspired nonlinear dynamics‑based adaptive controller achieves comparable ride comfort performance under random road excitations while significantly reducing energy consumption.