Controllable suspension sliding mode tracking controller taking vehicle steady state as reference

Abstract

The invention discloses a controllable suspension sliding mode tracking controller taking the vehicle steady state as a reference. The controller is applicable to various damp-adjustable vehicle air, oil and electromagnetism active suspensions as well as magneto-rheological semi-active suspensions. A vehicle body sprung mass of a vehicle stably running on a smooth road is taken as an ideal reference state, asymptotically stable sliding mode control is realized according to the dynamic error between the actual sprung mass motion state and the ideal reference state of a controlled suspension system, and the sliding mode surface adopts a combination of an integral term, a proportional term and a differential term of the dynamic error. By means of the sliding mode controller, the vertical movement suspension performance of the vehicle can be ideally improved, the structure is simple, the real-time performance is high, and engineering realization is easy.

Description

technical field [0001] The invention relates to the technical field of automobile vibration reduction control, in particular to a controllable suspension sliding mode tracking controller which takes the steady state of a vehicle as a reference. Background technique [0002] The suspension system is the key system to ensure the driving comfort and handling stability of the vehicle, which can be divided into three categories: passive suspension, semi-active suspension and active suspension. Among them, the traditional passive suspension system cannot take into account both comfort and handling. Therefore, semi-active suspension and active suspension based on variable damping or variable stiffness actuators have become a hot spot for domestic and foreign scholars and technicians in the past ten years. research direction. [0003] The fully hydraulic active suspension system and air suspension system based on linear optimal control are mature in technology and have good control...

AI Technical Summary

Problems solved by technology

Among them, the traditional passive suspension system cannot take into account both comfort and handling. Therefore, semi-active suspension and active suspension based on variable damping or variable stiffness actuators have become a hot spot for domestic and foreign scholars and technicians in the past ten years. research direction

[0003] The fully hydraulic active suspension system and air suspension system based on linear optimal control are mature in technology and have good control performance and have been commercially applied. However, their high cost, complex structure and high maintenance cost limit their further application; The controlled magneto-rheological semi-active suspension system has simple structure and good control effect, and has obtained some commercial applications. However, the switch control will cause nonlinear dynamics problems of the system, and it is difficult to obtain the comprehensive suspension performance similar to the full active suspension system.

Modern control methods such as optimal control, fuzzy control, and adaptive control that have been further developed can be effectively applied to vehicle controllable suspension systems in theory, but most of these methods have many design assumptions, many demand parameters, and poor real-time calculation. And other characteristics, there is a big difference from the actual control, most of them are only in the simulation calculation or laboratory test stage, and there is still a long way to go before the actual vehicle application, such as the magnetorheological control proposed by the Chinese invention patent (ZL201010144138. The hybrid semi-active variable structure control method of the intelligent vehicle suspension adopts the reference model of the ideal ceiling-controlled semi-active suspension system, and assumes that the road surface input excitation is approximately equal to the motion state of the unsprung mass, and the tracking process needs to go through a more complex The calculation process leads to low real-time control. The feedback state required by the controller includes multiple sets of displacement, velocity, and acceleration signals. Signal errors in actual applications can easily lead to control failure.

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