Tuning PID Controllers Using Artificial Intelligence Techniques.

Salem, Ahmed; Moustafa, Mohamed N.; Ammar, Mohammed E.

doi:10.21608/iceeng.2014.30369

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…At present, intelligent control system has been proposed for tuning by the artificial data processing and machine learning. Especially, the metheuristic method is the one of the artificial intelligence [23]. The metheuristic method becomes the effective tool for simulation and optimization of the parameters based on bio-inspired concept from the behavior of the animal, adopted to design the algorithm of the metheuristic method which is the modern optimization.…”

Section: Artificial Tuning Methodsmentioning

confidence: 99%

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Artificial Intelligent Tuning PI Controller on Wind Turbine System with Three-Phase Grid Connected System

Jaikhang¹,

Tunyasrirut²

2019

IJEEI

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In order to generate the electricity from the wind turbine system with a permanent magnet synchronous generator (PMSG) to the three-phase grid connected system, it is very challenging because the electricity generated from wind energy resource is inconstancy. In this paper, the electrical power between the two systems are regulated by PI controller. For tuning the gains of PI controller, artificial intelligent methods, particle swarm optimization (PSO), gravitational search algorithm (GSA), artificial neural networks (ANN), are applied. The experiments of the control systems are testing at 200 w and 400 w. The experimental results show that the rise time of an electrical power of control system at 200 w tuning gains of the PI controller by ANN combined with PSO is better than the traditional tuning methods, pole placement. Therefore, the proposed intelligent system can not only reduce the overshoot of the active power but also improve the response power.

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Section: Artificial Tuning Methodsmentioning

confidence: 99%

“…The gravitational search algorithm is the optimal method using the gravitational law with the knowledge of Newton's second law. Namely, the acceleration depends on the force on the object and the mass of that object as shown in (23).…”

Section: Gravitational Search Algorithmmentioning

confidence: 99%

Artificial Intelligent Tuning PI Controller on Wind Turbine System with Three-Phase Grid Connected System

Jaikhang¹,

Tunyasrirut²

2019

IJEEI

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“…By this combination, an adaptive control strategy can be obtained by online estimation to approximate the parameter varies corresponding to the unknown model [3]. For example, the proportional-integral-derivative (PID) control approach is combined with the artificial intelligence (AI) method to achieve adaptive intelligent control [4]. Similar kind to PID controller, the sliding mode controller (SMC) is also possibly be combined with AI approach to improving the control performance [5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy sliding mode controller for a single-stage inverted pendulum

Suprapto

Zakarijah

Muslikhin

2022

IJAAS

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Sliding mode controller (SMC) has become a popular traditional control method in industries due to the most effective control strategies employing nonlinear control and the ability to reject disturbances, particularly for line trajectory control. However, this control method has chattering problems due to high-frequency switching. To cope with the shortcoming, an artificial intelligence (AI) method is utilized in the traditional SMC to eliminate or reduce this chattering problem. This paper investigates an adaptive fuzzy logic system combined with SMC algorithm to alleviate the problem. Fuzzy logic is chosen due to its advantages in tackling nonlinear properties using if-then thinking, whereas SMC method can be applied due to its ability to reject disturbance control. The inverted pendulum is selected as a controlled object and simulated using MATLAB/Simulink to investigate this control method. By combining the fuzzy logic system and the SMC approach, the chattering problems can be adaptively reduced on the line trajectory tracking signal. The adaptive fuzzy SMC achieved better performance with fast response compared with previous literature algorithms for similar plants.

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Tuning PID Controllers Using Artificial Intelligence Techniques.

Cited by 2 publications

References 5 publications

Artificial Intelligent Tuning PI Controller on Wind Turbine System with Three-Phase Grid Connected System

Artificial Intelligent Tuning PI Controller on Wind Turbine System with Three-Phase Grid Connected System

Adaptive fuzzy sliding mode controller for a single-stage inverted pendulum

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