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

Sinthipsomboon, Kwanchai; Hunsacharoonroj, Issaree; Khedari, Josept; Po-Ngaen, Watcharin; Pratumsuw, Pornjit

doi:10.5772/48614

Cited by 14 publications

(7 citation statements)

References 1 publication

(3 reference statements)

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“…The FL was developed in the form of the Mamdani-type fuzzy inference system. The Mamdani-type was chosen due to previous successive applications, reported in related work [42][43][44]. The FL applied to the wave maker actuators was established with two inputs and one output.…”

Section: Model Of the Fuzzy-logic Controllermentioning

confidence: 99%

“…According to the functions defined, the FVE crisp value is quantified to the NF, NM, ZO, PM, PF fuzzy sets. The Λ-type membership functions were applied due to common use and proven efficiency [42][43][44]52]. The Γ-type and L-type of the membership functions were applied due to the thresholds of the sensors and actuators [40,42,52].…”

Section: Model Of the Fuzzy-logic Controllermentioning

confidence: 99%

“…It was hindering the model tests significantly. However, fuzzy-logic controller of Mamdani-type was successfully applied versus PI and PID controllers to achieve higher performance of electrohydraulic actuators in other applications [42][43][44]. The greatly satisfactory results reported there allowed us to expect improvement of the wave maker performance for the control system based on the fuzzy-logic controller, versus the hitherto applied cascading PI ones.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Control of Waves Generation in a Towing Tank

Drzewiecki

Guziński

2020

Energies

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This paper presents the results of research related to the transformation of electrical energy into potential and kinetic energy of waves generated on the water surface. The waves are generated to model the environmental conditions for the needs of the model tests. The model tests are performed on model-scale objects to predict the features of full-scale maritime objects. It is done to improve human safety and the survivability of constructions. Electrical energy is transformed into the energy of the water waves using a wave maker. The wave maker considered is a facility with an electrohydraulic drive and an actuator submerged into the water. The actuator movement results in the waves being mechanically-generated in accordance with the wave maker theory. The study aimed to investigate the advantage of the newly implemented fuzzy-logic controller over the hitherto cascading proportional-integral controllers of the wave maker actuator. The research was focused on experimental investigation of the transformation process outcomes harvested under the fuzzy-logic controller, versus the cascading proportional-integral controllers. The waves were generated and measured in the real towing tank, located in the Maritime Advanced Research Centre (CTO S.A.). The investigation confirmed the advantage of the fuzzy-logic controller. It provides more accurate transformation of energy into the desired form of the water waves of specified parameters—frequency and amplitude—and more flat amplitude-frequency characteristic of the transformation process.

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Section: Model Of the Fuzzy-logic Controllermentioning

confidence: 99%

Section: Model Of the Fuzzy-logic Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fuzzy Control of Waves Generation in a Towing Tank

Drzewiecki

Guziński

2020

Energies

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“…Similarly, implementation on control Liquid level. Classic PID parameters usually remain during operation, consequently, the controller becomes inefficient to control the system if there is an unknown or unknown interference the environment around the system changes (Sinthipsomboon, 2011). So the PID control is not sufficiently adaptive (O.…”

Section: Pid-controllermentioning

confidence: 99%

The Simulation Damping of Power System Oscillation using Phase-Compensator and PID-Controller in Single-Machine Infinite-Bus

Junaidi¹,

Salman²,

Rahmaniar³

et al. 2019

Proceedings of the Proceedings of the 5th Annual International Seminar on Trends in Science and Science Education, AISTSSE 2018

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The paper present the dynamic oscillation of the electric power system. The concept of system resilience that functions for machines that move normally and can return to a stable state after a disturbance occurs. Oscillation of changes in speed and oscillation changes in the electric power system occur due to disturbances. Disturbance in electricity causes an electric current that works on the system beyond the nominal current. The effect of the current disturbance will have an impact on changes in the current torque parameters that cause prime-over instability when the generator is operating. This instability will affect the rotor speed and the voltage emitted by the generator. Dynamic oscillation repair testing by applying phase compensation control and PID-Controller on the excitation system is done to see the response of speed and voltage response when the system is experiencing interference. Observation of system oscillation response using matlab simulation to see system performance. The simulation results show that dynamic stability improvement with phase compensation method can reduce oscillation speed and voltage within 6 seconds and the use of PID-controller can reduce the speed and voltage in 3 seconds. The phase compensation method and PIDcontroller applied to the excitation system can reduce the electric power system oscillation.

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“…Their performance is described as accurate when uncertainty and perturbations take place while performing a trajectory. Although the training periods are extremely long, there are also combinations of PID controls and a smart system aimed to auto-tune the gains of different systems such as: sub-aquatic [ 15 , 16 ], non linear [ 17 , 18 , 19 , 20 , 21 , 22 ], and others: [ 23 , 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Neural Network-Based Self-Tuning PID Control for Underwater Vehicles

Hernández-Alvarado

García-Valdovinos

Salgado-Jiménez

et al. 2016

Sensors

154

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For decades, PID (Proportional + Integral + Derivative)-like controllers have been successfully used in academia and industry for many kinds of plants. This is thanks to its simplicity and suitable performance in linear or linearized plants, and under certain conditions, in nonlinear ones. A number of PID controller gains tuning approaches have been proposed in the literature in the last decades; most of them off-line techniques. However, in those cases wherein plants are subject to continuous parametric changes or external disturbances, online gains tuning is a desirable choice. This is the case of modular underwater ROVs (Remotely Operated Vehicles) where parameters (weight, buoyancy, added mass, among others) change according to the tool it is fitted with. In practice, some amount of time is dedicated to tune the PID gains of a ROV. Once the best set of gains has been achieved the ROV is ready to work. However, when the vehicle changes its tool or it is subject to ocean currents, its performance deteriorates since the fixed set of gains is no longer valid for the new conditions. Thus, an online PID gains tuning algorithm should be implemented to overcome this problem. In this paper, an auto-tune PID-like controller based on Neural Networks (NN) is proposed. The NN plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. Simulation results are given considering an underactuated 6 DOF (degrees of freedom) underwater ROV. Real time experiments on an underactuated mini ROV are conducted to show the effectiveness of the proposed scheme.

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

Cited by 14 publications

References 1 publication

Fuzzy Control of Waves Generation in a Towing Tank

Fuzzy Control of Waves Generation in a Towing Tank

The Simulation Damping of Power System Oscillation using Phase-Compensator and PID-Controller in Single-Machine Infinite-Bus

Neural Network-Based Self-Tuning PID Control for Underwater Vehicles

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