Fuzzy gain scheduling of PID controller implemented on real time level control

Fini, Ali Motamed Oroaya; Gogani, Mahdi Bahar; Pourgholi, Mahdi

doi:10.1109/cfis.2015.7391640

Cited by 9 publications

(7 citation statements)

References 4 publications

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“…Therefore, the controller behavior may cause deterioration of the system performance. These drawbacks can be overcome by using an intelligent controller, such as fuzzy logic [24,25]. It has been found that fuzzy logic-based PID controllers have better capabilities of handling the previously mentioned systems.…”

Section: Introductionmentioning

confidence: 99%

Novel Fuzzy Controller for a Standalone Electric Vehicle Charging Station Supplied by Photovoltaic Energy

Zaid

Albalawi

Alatawi

et al. 2021

ASI

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The electric vehicle (EV) is one of the most important and common parts of modern life. Recently, EVs have undergone a big development thanks to the advantages of high efficiency, negligible pollution, low maintenance, and low noise. Charging stations are very important and mandatory services for electric vehicles. Nevertheless, they cause high stress on the electric utility grid. Therefore, renewable energy-sourced charging stations have been introduced. They improve the environmental issues of the electric vehicles and support remote area operation. This paper proposes the application of fuzzy control to an isolated charging station supplied by photovoltaic power. The system is modeled and simulated using Matlab/Simulink. The simulation results indicate that the disturbances in the solar insolation do not affect the electric vehicle charging process at all. Moreover, the controller perfectly manages the stored energy to compensate for the solar energy variations. Additionally, the system response with the fuzzy controller is compared to that with the PI controller. The comparison shows that the fuzzy controller provides an improved response.

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Section: Introductionmentioning

confidence: 99%

Novel Fuzzy Controller for a Standalone Electric Vehicle Charging Station Supplied by Photovoltaic Energy

Zaid

Albalawi

Alatawi

et al. 2021

ASI

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“…To resolve these conflicting issues, the gain scheduling method is somewhere applied [5], [6], which helps in choosing the optimal PIDC settings best satisfying the current range of plant variables. Nevertheless, gain scheduling cannot consider all possible system states to ensure overall robustness.…”

Section: Introductionmentioning

confidence: 99%

“…There are rather few publications about MIMO fuzzy PIDCs that convert two inputs, usually the speed error and its rate, directly into three PIDC settings: [9], [20] - [22]. A more common approach presented, in particular, in [6], [23] - [25] involves sharing of fuzzy operation among three independent controllers, namely, fuzzy-P, fuzzy-I, and fuzzy-D.…”

Section: Introductionmentioning

confidence: 99%

Speed Control of Electric Vehicle Propulsion with Autotuning at Changeable Driving Modes and Road Conditions

Aksjonov

Nedoma

Vodovozov

et al. 2019

2019 IEEE International Conference on Mechatronics (ICM)

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Considering the high demands continually imposed on equipment indispensable for intelligent transportation, this paper focuses on the cruise control in propulsion systems of road electric vehicles. The research lays emphasis on how to arrange optimal dynamics in terms of the speed overshoot and the speed rise time at changeable driving modes and road conditions. The paper addresses two aspects, namely, most accurate following the demanded transition process and most rapid achieving the setpoint. The former issue is typical for industrial vehicles operated in rather stable obstacles (loaders, forklift trucks, carriers, etc.), whereas the latter one concerns traditional road electric cars. Online autotuning of the controller is provided directly in the driving process by applying periodically estimated slope and peak input signals for analysing the speed responses and correcting controller settings. Tuning procedures based on binary logic and fuzzy logic approaches are compared. Keywords-road electric vehicle, propulsion, PID controller, binary logic controller, fuzzy logic controller, autotuning.I.

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“…To resolve these conflicting issues, the gain scheduling method is somewhere applied [5], [6], which helps in choosing optimal PIDC settings that best satisfy the current range of plant variables. Nevertheless, gain scheduling cannot consider all possible system states to ensure overall robustness.…”

Section: Introductionmentioning

confidence: 99%

“…There are rather few publications about fuzzy PIDCs capable to convert at least two inputs (usually, the speed error and its rate) directly into at least three PIDC settings [9], [16] - [18]. A more prevalent approach presented, in particular, in [6], [19] - [21] involves sharing of fuzzy operation among three independent controllers, namely, fuzzy P, fuzzy I, and fuzzy D.…”

Section: Introductionmentioning

confidence: 99%

Robust Speed Controllers with Autotuning for Electrically Driven Equipment

Aksjonov

Serbin²,

Vodovozov

et al. 2019

2019 26th International Workshop on Electric Drives: Improvement in Efficiency of Electric Drives (IWED)

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In the light of the growing demands for robustness of machine tools and apparatus equipment, this paper focuses on the speed control of electrically driven moving parts, such as supports, cars, loaders, forklift trucks, carriers, etc. The research lays emphasis on how to maintain identical dynamics in terms of the speed overshoot and the speed rise time at driving obstacles that cannot be confidently foreseen. This issue is typical for machines operated in rather stable conditions at moderate speeds those frictions, gaps, backlashes, or elasticity may change unpredictably during operation. Two autotuning procedures are designed and studied. The first one based on an iterative binary logic algorithm addresses the accurate following the demanded dynamics. The second one based on the one-step fuzzy logic approach provides rapid achieving the setpoint with rather good dynamics.

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Fuzzy gain scheduling of PID controller implemented on real time level control

Cited by 9 publications

References 4 publications

Novel Fuzzy Controller for a Standalone Electric Vehicle Charging Station Supplied by Photovoltaic Energy

Novel Fuzzy Controller for a Standalone Electric Vehicle Charging Station Supplied by Photovoltaic Energy

Speed Control of Electric Vehicle Propulsion with Autotuning at Changeable Driving Modes and Road Conditions

Robust Speed Controllers with Autotuning for Electrically Driven Equipment

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