Application of self-tuning fuzzy proportional–integral–derivative control in hydraulic crane control system

Hao, Wenrui; Kan, Jiangming

doi:10.1177/1687814016655258

Cited by 14 publications

(11 citation statements)

References 18 publications

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“…PID controller juga dapat di-tuning oleh FLC adaptive dengan pengaturan bentuk Membership Function (MF) [4]. Self-tuning fuzzy [5] dan fuzzy inference rule [6] telah diimp lementasikan pada tuning PID controller. Seluruh teknik tuning menargetkan performa respon transien yang terlihat pada settling time, rise time, percent overshoot, dan error steady state [7].…”

Section: Pendahuluanunclassified

Metode Tuning Operating Range Fuzzy PID Controller pada Sistem Orde Tiga

Sutarna

Purwanti

2020

Jurnal Teknik Elektro

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This research discusses the development of a model Fuzzy Proportional, Integral, Derivative (Fuzzy PID) controller models and self-tuning. This method has been implemented in the third-order system of Differential Equations, as a sample implementation of a PID controller. The methods self-tuning known are fuzzy rules, membership function (MF), and scaling factor. The focus of the discussion in this research is to introduce self-tuning to the operating range (OR) setting of MF. Previous research has succeeded in converting a PID controller to a Fuzzy Logic Controller (FLC) which is in accordance with the PID structure. The FLC has three inputs and one output as in the PID controller, hereinafter referred to as Fuzzy PID controller. Knowledgebase on the FLC structure of three inputs one output is expressed in the form of cubic fuzzy associative memory (FAM). The conversion was done by mapping errors, integrals error, derivative errors and outputs of PID controller into the OR of MF Fuzzy input/output. The size of the OR conversion value on the MF fuzzy input was set, so the response transient is set-to-point. While the OR value of the MF fuzzy output was fixed as a limitation. Improved settling time was reached up to 75.3% and percent overshoot was reduced by 57.7% in Fuzzy PID with PID controller. The output signal from the Fuzzy PID controller showed the smallest amplitude of 24.12, while the PID controller was 32.53. The amplitude unit depends on the Fuzzy PID controller parameters when it applied the real plant. The third-order Fuzzy PID controller has been successfully simulated in Simulink/Matlab.

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Section: Pendahuluanunclassified

Metode Tuning Operating Range Fuzzy PID Controller pada Sistem Orde Tiga

Sutarna

Purwanti

2020

Jurnal Teknik Elektro

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“…17 A fuzzy PID controller, which has advantage over traditional PID controllers, was utilized to reduce hydraulic pressure oscillation in hydraulic crane system. 18 A mathematical model of the servo drive hydraulic control was established, and an algorithm of controlling the nonlinear object was adapted using the linearization method of the model process to compensate disruptions like friction and changeable load powers mass. 19 For a single-ended cylinder in a pump displacement controlled circuit, circuit arrangement is necessary in order to balance unequal flow rates entering and leaving the cylinder volumes.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel miniature hydraulic actuation system and offset to long hose effect

Wang

Cao

Zhang

2018

Advances in Mechanical Engineering

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For its compact and flexible design, a novel miniature hydraulic actuation scheme is proposed for use in applications especially where both size and power are extremely important. The system works on a volume-controlled method using miniature cylinders. In order to describe the impact of hose deformation on the system, a lumped-parameter hose model is proposed, and coefficients in the model are determined on the basis of experiments with an existing prototype. A position tracking controller with a disturbance observer is designed for a miniature hose-connecting hydraulic actuation system. Tracking control for the target displacement is arranged as an external circuit of pressure compensation to eliminate the tracking error and an inner circuit of pressure compensation which operates by observed disturbances and oil pressure in the hose. Lyapunov theory is employed to verify the stability of the system with the disturbance observer. The disturbance observer-based controller has much better tracking performance than conventional proportional-integral-derivative controllers, which can substantially offset negative effects of the hose.

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“…Due to simple structure and easy implementation, PID control has been commonly used in hydraulic systems [9,10]. On this basis, some researchers developed accurate fuzzy PID and PSO-PID controllers [11][12][13][14]. A robust fixed-gain linear output pressure controller was designed for a double-rod electrohydrostatic actuator using quantitative feedback theory (QFT) to provide desired transient responses, tracking bandwidth, robust stability, and disturbance rejection for the closed-loop system [15].…”

Section: Introductionmentioning

confidence: 99%

Position Control with ADRC for a Hydrostatic Double-Cylinder Actuator

Wang

Chang

2020

Actuators

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A compact and flexible hydraulic double-cylinder actuation scheme is proposed for use in applications, especially where power density is extremely demanding. In view of flexible amounting requirements, long and thin hoses were utilized to connect two cylinders. Affecting the actuation preciseness, volume variation of the hoses caused by pressurized oil and bubbles was the main problem the system encountered. In this study, an active disturbance rejection control (ADRC) strategy was adopted for the improvement of displacement control performance under uncertain external load. After the experimental verification of the necessity of a hose model for the system, a centralized-parameter hose model was constructed where the coefficients are determined on the basis of the experimental data. Additionally, the system and the controller proposed were mathematically modeled. Simulation results shows that the system using ADRC exhibited higher displacement accuracy and better dynamic performance than that using PID (Proportion-Integral-Derivative) or fuzzy PID. ADRC has a stronger disturbance rejection ability. ADRC is an effective solution to nonlinear control of systems with uncertain parameters or various loads.

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Application of self-tuning fuzzy proportional–integral–derivative control in hydraulic crane control system

Cited by 14 publications

References 18 publications

Metode Tuning Operating Range Fuzzy PID Controller pada Sistem Orde Tiga

Metode Tuning Operating Range Fuzzy PID Controller pada Sistem Orde Tiga

A novel miniature hydraulic actuation system and offset to long hose effect

Position Control with ADRC for a Hydrostatic Double-Cylinder Actuator

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