A Hybrid of Fuzzy and Proportional-Integral-Derivative Controller for Electro-Hydraulic Position Servo System

Pratumsuwan, Pornjit; Thongchai, Siripun; Tansriwong, Surapun

doi:10.3844/erjsp.2010.62.67

Cited by 43 publications

(22 citation statements)

References 10 publications

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“…A numbers of successful applications have been reported and these applications of the fuzzy control have often produced results superior to those of classical control (Pratumsuwan et al, 2010). This increased popularity of the fuzzy control can be attributed to the fact that fuzzy logic systems provide a powerful vehicle that allows engineers to incorporate human reasoning in the control algorithm.…”

Section: Control Scheme For Ssscmentioning

confidence: 99%

Fuzzy Logic Controller for Static Synchronous Series Compensator with Energy Storage System for Transient Stability Analysis

Padma¹

2011

Journal of Computer Science

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Problem statement: FACTS devices play a major role in the efficient operation of the complex power system. FACTS devices such as STATCOM, SSSC and IPFC are in increasing usage. With energy storage systems they have a good control over the real as well as reactive power compensation and transient stability improvement. The design of controller for the SSSC with SMES system is analyzed in this study. Approach: The main variables to be controlled in the power system for efficient operation are the voltage, phase angle and impedance. A SSSC is a series connected converter based FACTS control which can provide a series reactive power compensation for a transmission system. With the addition of energy storage device, in addition to the reactive power compensation the real power exchange is also accomplished. Fuzzy logic controller is designed for the efficient operation of the power system with SSSC integrated with energy storage device. From the power reference the current reference is calculated and the error and change in error in the current are calculated in the controller. Results: A three phase to ground fault is simulated in the test system. A comparative analysis of the PI and fuzzy logic control of SSSC with energy storage system for the rotor angle oscillation damping following the disturbance is done. Conclusion: The fuzzy logic controller works efficiently compared to the conventional PI controller for the SSSC with SMES system. Also with energy storage system in the FACTS devices, the efficient operation of the power system is possible.

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Section: Control Scheme For Ssscmentioning

confidence: 99%

Fuzzy Logic Controller for Static Synchronous Series Compensator with Energy Storage System for Transient Stability Analysis

Padma¹

2011

Journal of Computer Science

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“…The approach begins with judicious selection of neural network models which are trained off line to learn the inverse and forward models of each channel of the furnace. The training patterns are obtained from the input output behavioral characteristic of each channel of the process (Malar and Thyagarajan, 2009 (Pratumsuwan et al, 2010). Fuzzy logic provides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge based systems.…”

Section: Temperature System In Plastic Extrusion Modelmentioning

confidence: 99%

Design of Synthetic Optimizing Neuro Fuzzy Temperature Controller for Dual Screw Profile Plastic Extruder Using Labview

Samikannu¹,

Poonamallie²

2011

Journal of Computer Science

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Problem statement:The temperature control in plastic extrusion machine is an important factor to produce high quality plastic products. The first order temperature control system in plastic extrusion comprises of coupling effects, long delay time and large time constants. Controlling temperature is very difficult as the process is multistage process and the system coupled with each other. In order to conquer this problem the system is premeditated with neuro fuzzy controller using LabVIEW. Approach: The existing technique involved is conventional PID controller, Neural controller, mamdani type Fuzzy Logic Controller and the proposed method is neuro fuzzy controller. Results: Manifest feature of the proposed method is smoothing of undesired control signal of conventional PID, neural controller and mamdani type FLC controller. The software incorporated the LabVIEW graphical programming language and MATLAB toolbox were used to design temperature control in plastic extrusion system. Hence neuro fuzzy controller is most powerful approach to retrieve the adaptiveness in the case of nonlinear system. Conclusion: The tuning of the controller was synchronized with the controlled variable and allowing the process at its desired operating condition. The results indicated that the use of proposed controller improve the process in terms of time domain specification, set point tracking and also reject disturbances with optimum stability.

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“…For example, they are the highly nonlinear phenomena such as fluid compressibility, the flow/pressure relationship and dead-band due to the internal leakage and hysteresis, and the many uncertainties of hydraulic systems due to linearization. Therefore, it seems to be quite difficult to perform a high precision servo control by using linear control method Rong-Fong Fung et al, 1997;Aliyari et al, 2007;Pratumsuwan et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…KP, KI, and KD, are usually fixed during operation. Consequently, such a controller is inefficient for control a system while the system is disturbed by unknown facts, or the surrounding environment of the system is changed (Panichkun & Ngaechroenkul, 2000;Pratumsuwan et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…However, PID controller is better able to control and minimize the steady state error of the system. To enhance the controller performance, hybridization of these two controller structures comes to one mind immediately to exploit the beneficial sides of both categories, know as a hybrid of fuzzy and PID controller (Panichkun & Ngaechroenkul, 2000;Pratumsuwan et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Hybrid of Fuzzy and Fuzzy Self-Tuning PID Controller for Servo Electro-Hydraulic System

Sinthipsomboon¹,

Hunsacharoonroj²,

Khedari³

et al. 2012

Fuzzy Controllers- Recent Advances in Theory and Applications

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A Hybrid of Fuzzy and Proportional-Integral-Derivative Controller for Electro-Hydraulic Position Servo System

Cited by 43 publications

References 10 publications

Fuzzy Logic Controller for Static Synchronous Series Compensator with Energy Storage System for Transient Stability Analysis

Fuzzy Logic Controller for Static Synchronous Series Compensator with Energy Storage System for Transient Stability Analysis

Design of Synthetic Optimizing Neuro Fuzzy Temperature Controller for Dual Screw Profile Plastic Extruder Using Labview

A Hybrid of Fuzzy and Fuzzy Self-Tuning PID Controller for Servo Electro-Hydraulic System

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