基于模糊增益调度的悬架自适应控制

Gui-hong Xu, Tao Sun
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引用次数: 0

摘要

结合LQG和模糊逻辑控制器(LFLC),提出了一种适应车速和路况的新型控制算法,解决了传统悬架在平顺性、操控性和包装要求之间的冲突。LFLC跟踪悬架工作空间和车身加速度随路况和车速变化的信号,动态调节性能指标的权重,以调度LQG控制器的增益,实现多个控制目标。仿真结果表明,与被动悬架和传统LQG控制系统相比,LFLC在不违反给定悬架挠度限制的情况下,能有效提高车辆在不同速度和路况下的平顺性和安全驾驶性能。
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Adaptive control of suspension based on Fuzzy logic gain scheduling
The new control algorithm combining LQG and Fuzzy logic controller (LFLC) adapted to vehicle speed and road conditions is proposed to compromise the classical suspension conflict between ride comfort, handling and packaging requirements. Tracking the signals of the suspension working space and body acceleration that vary sharply with the variation of road conditions and vehicle speed, LFLC can regulate the weights of the performance indexes dynamically to schedule the gain of the LQG controller for achieving multiple control objectives. Compared with the passive suspension and the conventional LQG control system, the simulation results demonstrate that LFLC can improve effectively the ride comfort and safe drivability at different speeds or road conditions without violating the given suspension deflection limit.
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