Evidence map›Paper›PMID 38610466›Full record

ArticleSensors (Basel, Switzerland)2024

Model Predictive Control for Speed-Dependent Active Suspension System with Road Preview Information.

Qiangqiang Li, Zhiyong Chen, Haisheng Song, Yahui Dong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qiangqiang LiThe State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130012, China.
Zhiyong ChenThe State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130012, China.
Haisheng SongThe Vehicle and Traffic Engineering, Henan Institute of Technology School, Zhengzhou 453003, China.
Yahui DongShaanxi Heavy Duty Automobile, Xi'an 710299, China.

Funding

National Key Research and Development Program of China 2018YFB0106200
6 · The paper itself

Abstract

This paper proposes a model predictive control (MPC) scheme based on linear parameter variation to enhance the damping control of speed-dependent active suspensions. The controller is developed by introducing a speed-dependent term, specifically front- and rear-wheel time delays, to the half-car model using the Padé approximation. Subsequently, the model is augmented with time-varying parameter dependence. An adaptive Kalman filter based on variance matching is employed to estimate system states affected by imprecise sensor measurement noise. Finally, a set of explicit control laws incorporating road preview information and available vehicle speed are determined offline using multi-parameter linear programming (mp-LP), simplifying online implementation to searching for optimal solutions in a lookup table. Simulation results demonstrate a significant improvement in active suspension control under changing vehicle speeds compared to passive control.

Indexed as

active suspensionlinear parameter varying (LPV)model predictive control (MPC)road preview information

Identifiers

PMID38610466
PMCPMC11014201

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.