Fuzzy Control for Automatic Train Operation System

Yasunobu, Seiji; Miyamoto, Shigenobu; Ihara, Hirokazu

doi:10.1016/b978-1-4832-1450-4.50040-7

Cited by 25 publications

(17 citation statements)

References 3 publications

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“…Fuzzy logic has been used in several fields to tackle complex problems and essentially mimics human way of thinking and analyzing [9]. Fuzzy logic has been used in several practical applications, e.g., automatic operation and control of trains [10] [11] [12] [13] [14]. We can design a fuzzy controller either as a standalone one or in conjunction with conventional control to improve performance of a hitherto poor controller.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems

Kumar¹,

Sharma²

2018

IJISA

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This work aims at designing a fractional Proportional-Integral-Derivative controller wherein we hybridize a genetic algorithm based fractional Proportional-Integral-Derivative controller with a fuzzy logic Proportional-Integral-Derivative controller. We attempt at optimizing the fractional order Proportional-Integral-Derivative controller parameters by incorporating a Genetic Algorithm based mechanism. Thereafter, the optimized genetic algorithm based fractional Proportional-Integral-Derivative control is further fine tuned and hybridized to a fuzzy Proportional-Integral-Derivative control. Here, fuzzy logic based inference mechanism is used to tackle system uncertainties and use of rule firing strengths produces an adaptive control. Genetic Algorithm has been used to generate the most optimal controller by a natural selection of the fittest. Amalgamating Genetic Algorithm and fuzzy control approaches on fractional order systems produces a highly efficient and noise tolerant control regime. We give simulation results and compare our hybrid approach against conventional and fractional Proportional-Integral-Derivative approaches on various integer and fractional order systems (with dead time) to elucidate its superiority and effectiveness.

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Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems

Kumar¹,

Sharma²

2018

IJISA

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“…Actually, Seiji Yasunobu has created a suitable control method by predictive fuzzy control which samples a skilled operator's operating knowledge, and it actually applied to subway in Sendai as Automatic Train Operation system [1], [2]. It indicated that it could realyze the smooth stopping of train at scheduled time by predictive fuzzy control.…”

Section: Introductionmentioning

confidence: 99%

A proposal of intelligent operating method considering the change of constraint conditions

Takahashi

Yasunobu

2012

The 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced In

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Train plays an important role as public transportation in our daily life. However, if transport volume decreased due to irregularities in the timetable of train, it'll be shock to our society. In that case, it is needed for train operators to recover the transport volume by their operating skills. In this study, we proposed an operating method considering the change of constraint conditions by intelligent control using an intelligent operating support system based on operating knowledge of expert operators in the dynamic environment. By providing appropriate support information to operators, it is confirmed that the proposed method is effective for shortening arrival time and the recovery of transport volume in such environment.

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“…Yasunobu et al [26] proposed a fuzzy ATO controller and implemented it in Sendai of Japan in 1987. This controller can control each train's departure, speed regulation, and dwell time.…”

Section: A Fuzzy and Evolutionary Algorithmsmentioning

confidence: 99%

A survey on optimal trajectory planning for train operations

Wang

Ning

Cao

et al. 2011

Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics

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Abstract-Because of the rising energy prices and environmental concerns, the calculation of energy-optimal reference trajectories for trains is significant for energy saving. On the other hand, with the development automatic train operation (ATO), the optimal trajectory planning is significant to the performance of train operation. In this paper, we present an integrated survey of this field. First, a nonlinear continuoustime train model and a continuous-space model of train operations are described, after which the optimal trajectory planning problem is formulated based on these two models. The various approaches in the literature to calculate the reference trajectory are reviewed and categorized into two groups: analytical solutions and numerical optimization. Finally, a short discussion of some open topics in the field of optimal trajectory planning for train operations are given.

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Fuzzy Control for Automatic Train Operation System

Cited by 25 publications

References 3 publications

A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems

A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems

A proposal of intelligent operating method considering the change of constraint conditions

A survey on optimal trajectory planning for train operations

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