Design method of adaptive inversion controller in flexible active suspension system

Abstract

The invention discloses a design method of an adaptive inversion controller in a flexible active suspension system. The method comprises the following steps of: 1, establishing an active suspension model; and 2, designing an adaptive inversion controller based on a neural network; and aiming at a two-degree-of-freedom flexible active suspension system with unknown nonlinear dynamics, in the control design of the automobile active suspension system, selecting a BL function to construct a control condition meeting system stability, and meanwhile, introducing a second-order auxiliary system to realize asymmetric control saturation compensation. Through the method, the adaptive inversion controller based on the neural network is designed and obtained; and hardware loop experiments show that compared with traditional PD and LQR control, the control method can better attenuate vertical vibration of sprung mass in the automobile active suspension system under sine and impact excitation in thecontrol design of the automobile active suspension system, and meanwhile grounding performance of the automobile active suspension system is improved.

Description

technical field [0001] The invention belongs to the field of automatic control of automobiles, and in particular relates to a design method of an adaptive inversion controller in a flexible active suspension system. Background technique [0002] The car suspension system is a key part of the car, which can improve the shimmy and comfort of the car during use. In addition to attenuating the vibration transmitted from the road surface disturbance to the car body, the suspension system must also ensure the dynamic travel of the suspension and the grounding. It is very important to study advanced active control methods to realize the vibration control of the suspension system. In the research process of the automobile suspension system, some research results have been obtained: for example, the research of the automobile suspension system The network control of the active suspension, and reduce the communication burden through the event trigger mechanism; and propose a class of ...

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Problems solved by technology

[0004] However, since the actual suspension system contains unknown nonlinear dynamics, ideal feedback linearization is difficult to implement, and in the prior art, an extended state observer is used to estimate the unknown dynamics of the system, which requires the unknown dynamics to be Lipschitz continuous and bounded; although There are adaptive fuzzy and neural network control methods proposed for the uncertainty of the suspension system, but most of the research is based on numerical simulation, and only stays at the level of simulation, and the related hardware loop experiments are still comparatively difficult. rare;

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