# H-infinity Filtering for Cloud-Aided Semi-active Suspension with Delayed Information

## TL;DR

This paper develops an H-infinity filtering approach for cloud-assisted semi-active vehicle suspension systems that accounts for time-varying delays in data transmission, enhancing state estimation accuracy.

## Contribution

It introduces a novel H-infinity filter design incorporating delayed cloud data for semi-active suspension systems using LMIs.

## Key findings

- Effective fusion of cloud and onboard data demonstrated in simulations.
- Robustness of the filter against bounded delays shown.
- Improved suspension state estimation accuracy achieved.

## Abstract

This chapter presents an H-infinity filtering framework for cloud-aided semiactive suspension system with time-varying delays. In this system, road profile information is downloaded from a cloud database to facilitate onboard estimation of suspension states. Time-varying data transmission delays are considered and assumed to be bounded. A quarter-car linear suspension model is used and an H-infinity filter is designed with both onboard sensor measurements and delayed road profile information from the cloud. The filter design procedure is designed based on linear matrix inequalities (LMIs). Numerical simulation results are reported that illustrates the fusion of cloud-based and on-board information that can be achieved in Vehicleto- Cloud-to-Vehicle (V2C2V) implementation.