Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Studies on vehicle active suspension based on LMS adaptive algorithm
The active control suspension system can improve both the riding comfort and handling safety in various operation conditions. In this paper, according to the evaluation method of riding comfort and handling safety of vehicle, the acceleration of the sprung mass, dynamic tyre load between wheels and the unsprung mass are determined as the evaluation targets of suspension performance. The least mean squares (LMS) adaptive algorithm is used in active suspension system. With adjusting the weight of the adaptive filter, the minimum quadratic performance index is obtained. For two-DOF vehicle suspension model, the sky-hook control, generalized adaptive control and LMS adaptive control are studied. The simulation results show that LMS adaptive control algorithm is not only simple but also remarkably effective.
Studies on vehicle active suspension based on LMS adaptive algorithm
The active control suspension system can improve both the riding comfort and handling safety in various operation conditions. In this paper, according to the evaluation method of riding comfort and handling safety of vehicle, the acceleration of the sprung mass, dynamic tyre load between wheels and the unsprung mass are determined as the evaluation targets of suspension performance. The least mean squares (LMS) adaptive algorithm is used in active suspension system. With adjusting the weight of the adaptive filter, the minimum quadratic performance index is obtained. For two-DOF vehicle suspension model, the sky-hook control, generalized adaptive control and LMS adaptive control are studied. The simulation results show that LMS adaptive control algorithm is not only simple but also remarkably effective.
Studies on vehicle active suspension based on LMS adaptive algorithm
Jianmin Sun, (Autor:in) / Qingmei Yang, (Autor:in) / Fengying Sun, (Autor:in) / Baoshan Ma, (Autor:in)
01.01.2003
331724 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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