Event trigger state estimating system based on markovian jumping

Abstract

The invention relates to an event trigger state estimating system based on markovian jumping. The system comprises a sensor sampling unit comprising a vehicle-mounted sensor used for collecting vehicle suspension system state information, an event trigger unit comprising an event trigger detector used for receiving measured data of the vehicle-mounted sensor on the basis of a periodic event trigger mechanism, a quantizer quantification unit comprising multiple communication links connected with the event trigger detector, connected with one another in parallel and each provided with a logarithmic quantizer, and an estimator network unit comprising estimators connected with the logarithmic quantizers on the communication links respectively used for conducting information transmission through a network. Compared with the prior art, the event trigger state estimating system based on markovian jumping has the advantages that parameters are easy to determine, the object estimating requirements are simple, network blocking is prevented, design is flexible, network resources are saved, external interference is resisted, and the like.

Description

technical field [0001] The invention relates to the field of automobile state estimation system and design, in particular to an event-triggered state estimation system based on Markov transition. Background technique [0002] As one of the main elements of road traffic, the performance of cars directly affects the safety of vehicles and people in the traffic system. The control and estimation strategies of the suspension system, which is an important part of the vehicle, have received more and more attention. The question of how rotation and suspension motion affect ride performance was studied in the early 1930s. With the rapid development of the suspension system, mathematical simulation and computer technology began to be applied in the field of suspension system research. In recent years, a large number of studies on suspension control systems have emerged. On the one hand, it will be difficult to maneuver the vehicle due to wear and collisions between the components ...

AI Technical Summary

Problems solved by technology

However, in some cases, the system reaches a steady state and there are no external disturbances, performing tasks periodically wastes the computational and energy resources of battery-based devices.

Moreover, if a sampling period tends to zero, a large number of redundant sampling signals are released to the shared communication network with limited bandwidth, which will cause network traffic congestion

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