Fuzzy controllers for tire slip control in anti-lock braking systems

Precup, Radu‐Emil; Preitl, Ștefan; Bălaş, Marius M.; Balas, Valentina E.

doi:10.1109/fuzzy.2004.1375359

Cited by 52 publications

(16 citation statements)

References 11 publications

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“…The performance of the FMRLC-based ABS is demonstrated by simulation for various road conditions (wet asphalt, icy) and "split road conditions" (the condition where, e.g., emergency braking occurs and the road switches from wet to icy or vice versa). Precup et al [70] developed a Takagi-Sugeno fuzzy controller and an interpolative fuzzy controller for tire slip control in ABS systems. By employing local linearized models of the controlled plant, the local controllers are developed in the frequency domain.…”

Section: Intelligent Control Based On Fuzzy Logicmentioning

confidence: 99%

An Antilock-Braking Systems (ABS) Control: A Technical Review

Aly¹,

Zeidan²,

Hamed³

et al. 2011

ICA

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Many different control methods for ABS systems have been developed. These methods differ in their theoretical basis and performance under the changes of road conditions. The present review is a part of research project entitled “Intelligent Antilock Brake System Design for Road-Surfaces of Saudi Arabia” In the present paper we review the methods used in the design of ABS systems. We highlight the main difficulties and summarize the more recent developments in their control techniques. Intelligent control systems like fuzzy control can be used in ABS control to emulate the qualitative aspects of human knowledge with several advantages such as robustness, universal approximation theorem and rule-based algorithms

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Section: Intelligent Control Based On Fuzzy Logicmentioning

confidence: 99%

An Antilock-Braking Systems (ABS) Control: A Technical Review

Aly¹,

Zeidan²,

Hamed³

et al. 2011

ICA

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“…The results presented in Figure 6 are encouraging. However, different conclusions are expected to be obtained for other applications [33][34][35][36][37][38][39][40].…”

Section: Analysis Of Translation Resultsmentioning

confidence: 99%

Evolving Fuzzy Models for Automated Translation

2017

APH

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“…3 are given as the average value of the best five runs of both algorithms. The conclusions can be different for other controllers [26]- [29] and for fuzzy models of other nonlinear processes [30]- [34]. …”

Section: Experimental Validationmentioning

confidence: 99%

Particle Swarm Optimization of fuzzy models for Anti-Lock Braking Systems

Precup

Sabau

Dragoş

et al. 2014

2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

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This paper suggests a Particle Swarm Optimization (PSO) approach to the optimal tuning of fuzzy models for Antilock Braking Systems (ABSs). A set of ten local state-space models of the ABS is first obtained by the linearization of the nonlinear state-space model of the ABS process at ten operating points. The initial Takagi-Sugeno (T-S) fuzzy models are next obtained by the modal equivalence principle, namely by placing the local state-space models of the process in the rule consequents. The optimization problem targets the minimization of the objective function (OF) expressed as the mean squared modeling error, and the vector variable of the OF consists of the feet of the triangular input membership functions. A PSO algorithm solves the optimization problem and gives the optimal T-S fuzzy models. A set of real-time experimental results is included to validate the PSO approach and the optimal T-S fuzzy models for real-world ABS laboratory equipment.

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Fuzzy controllers for tire slip control in anti-lock braking systems

Cited by 52 publications

References 11 publications

An Antilock-Braking Systems (ABS) Control: A Technical Review

An Antilock-Braking Systems (ABS) Control: A Technical Review

Evolving Fuzzy Models for Automated Translation

Particle Swarm Optimization of fuzzy models for Anti-Lock Braking Systems

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