Apply a Fuzzy Algorithm to Control an Active Suspension in a Quarter Car by Matlab’s Simulink

Hùng, Nguyễn Tấn; Nhung, Nguyen Thi Bich; Vu, Lu Thi Yen; Khai, Vu Quang; Son, Tran Anh; Thanh, Trương Quốc

doi:10.4028/www.scientific.net/amm.902.23

Cited by 6 publications

(5 citation statements)

References 11 publications

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“…The fault location measurement of sensor nodes has become one of the most important key technologies. With the development of power control technology in wireless sensor network, fault location measurement technology of sensor nodes has become a new research hotspot (Hung et al 2020). This paper focuses on the research of fault location measurement of sensor nodes based on fuzzy control algorithm.…”

Section: Discussionmentioning

confidence: 99%

Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

2021

Preprint

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Aiming at the problems of the traditional fault location measurement method for sensor nodes, such as more energy consumption and longer measurement time, a fault location measurement method for sensor nodes based on fuzzy control algorithm is designed and proposed. First of all, the fuzzy control algorithm is analyzed; then the clustering based on cluster head diagnosis is carried out for the network, that is, the nodes that meet the cluster head conditions and are set as normal cluster heads are selected as cluster heads. Finally, combined with the fuzzy control algorithm, the fault location of each cluster member node is measured directly by cluster head nodes. The simulation results show that the proposed method has good performance.

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Section: Discussionmentioning

confidence: 99%

Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

2021

Preprint

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“…Results show that the ride comfort of the vehicle improved due to the reduction in sprung mass acceleration [54]. Hung et al proposed the fuzzy logic controller for a quarter car of springmass damper system using MATLAB/Simulink, which provided good vehicle stability and ride comfort [55].…”

Section: Fuzzy Logic Control Systemmentioning

confidence: 99%

A Review on Various Control Strategies and Algorithms in Vehicle Suspension Systems

Ferhath,

Kamalakkannan Kasi

2023

Int. J. Automot. Mech. Eng.

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Automotive suspension systems provide passenger safety, ride comfort and vehicle handling in passenger and commercial vehicles. Through extensive research in the last couple of decades coupled with the recent advancements in technology, the improvement in vehicle handling and ride comfort have been significant by using various control strategies in semi-active and fully active suspension systems. Despite a significant number of articles available on the enhancement and improvement of vehicle suspension systems, there is certainly a lack of knowledge on various control strategies and algorithmic techniques used in the vehicle suspension system. Thereby, to address the gap, this review consecutively attempts to comprehensively explore the various research work conducted on the various control strategies used in vehicle suspension systems.

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“…As a result, the ANFIS controller, when used in conjunction with a neural network and a fuzzy controller, has a higher capacity due to its ability to learn from mathematical results [10]. Based on the selected Membership fuctions shapes and input-output pairs, the structure and fuzzy if-then rules of FIS in the ANFIS controller are automatically constructed based on the neural network learning algorithm.…”

Section: Icacc-2021mentioning

confidence: 99%

Performance Comparison of Various controllers on Semi-Active Vehicle Suspension System

Walavalkar¹,

Tandel²,

Thakur³

et al. 2021

ITM Web Conf.

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The value of a self-tuning adaptive semi-active control scheme for automotive suspension systems is discussed in this paper. The current vehicle suspension system uses fixed-coeffcient springs and dampers. The ability of vehicle suspension systems to provide good road handling and improve passenger comfort is usually valued. Passive suspension allows you to choose between these two options. Semi-Active suspension(SAS), on the other hand, can provide both road handling and comfort by manipulating the suspension force actuators directly. The semi-active suspension system for a quarter car model is compared to passive and various controllers such as Proportional-Integral, Proportional-Integral-Derivative, Internal model control (IMC)-PID, IMC-PID with filter, FUZZY, and Adaptive-network-based fuzzy inference system(ANFIS) in this analysis. This research could be relevant in the future for designing better car suspension adjustments to eliminate vertical jerks and rolling motion experienced by the vehicle body on bumps and humps.

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Apply a Fuzzy Algorithm to Control an Active Suspension in a Quarter Car by Matlab’s Simulink

Cited by 6 publications

References 11 publications

Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

A Review on Various Control Strategies and Algorithms in Vehicle Suspension Systems

Performance Comparison of Various controllers on Semi-Active Vehicle Suspension System

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