Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

Ali, Ahmed Abdul Hussein; Lateef, Rana Abdul Rahman; Saeed, Mahmood Wael

doi:10.1016/j.jestch.2017.08.001

Cited by 10 publications

(3 citation statements)

References 37 publications

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“…The fuzzy controller's control rules are frequently based on experts' experiences and are expressed as IF-THEN rules that link input and output variables. The IF-THEN rule is as follows [14]: IF e is NH and er, then u is PH The fuzzy logic system's input and output variables are represented by e, er, and u (error, error change, and output) may reduce the number of control rules for the beam vibration control system using this strategy. The vibration control system is listed in Table 1.…”

Section: Fuzzy Inference and Fuzzy Rulesmentioning

confidence: 99%

Intelligent Tuning Control of two Link Flexible Manipulator with Piezoelectric Actuator

Ali

2022

alkej

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This paper represents an experimental study on the application of smart control represented by the use of the fuzzy logic controller. Two-link flexible manipulators that are used in airspace and military applications are made of flexible materials characterized by low frequency and damping ratio. To solve this problem, this paper proposes the use of smart materials (piezoelectric transducers), where each link is bonded with a pair of piezoelectric transducers that act as a sensor and another as an actuator. As the arm vibrates because of the movement generated by the motor, this voltage is controlled by a regulator inside the LABVIEW® 2020 software and sends the output control voltage to the piezoelectric actuator. Experimental results show that fuzzy logic control was efficient during high amplitude and led to pronounced results in suppressing vibrations within a short time. Fuzzy logic gives more flexibility to the designer and allows him to control the system through its simple implementation. This differs from classical control, which requires a mathematical model.

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Section: Fuzzy Inference and Fuzzy Rulesmentioning

confidence: 99%

Intelligent Tuning Control of two Link Flexible Manipulator with Piezoelectric Actuator

Ali

2022

alkej

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“…Nevertheless, intelligent and expert based fuzzy logic controllers are considered to be effective tools for control of nonlinear complex systems such as multi-degree of freedom of structural systems with vibration damping problems [18][19][20][21][22][23][24][25][26][27]. Additionally, the reported works also show that the genetic algorithm and robust based fuzzy logic controllers have very successful results on the same issue [28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

A Novel Design of Interval Type-2 Neuro-Fuzzy Controller for Flexible Structure

Tınkır

Kalyoncu

Sezgen

2021

mech

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The aim of this research is to develop a novel design of interval type-2 neuro-fuzzy (IT2NF) controller for active vibration control of a flexible structure during an earthquake. For this purpose, two adaptive neural network based fuzzy logic controllers are designed and combined to create the novel design of an IT2NF controller to reduce the vibrations of two-storey flexible building model that occur during earthquake disturbance effects. Accordingly, dynamic modeling of a flexible structure is realized and simulated using the MATLAB / SimMechanics. Then, an experimental setup consisting of two-storey flexible structure, active mass damper (AMD) and shaker is established. Additionally, IT2NF controller is implemented in simulation and experimental models, and the effectiveness and performance of the IT2NF controller are tested under the scaled Northridge Earthquake acceleration. The obtained simulations and experimental responses are evaluated in terms of cart displacements, deflections, and accelerations of the flexible floors showing a good agreement between the simulations and the experimental results. The results show that the designed novel IT2NF controller reduced the total deflections of first and second floor by 72.3% and 68.7%, respectively, when compared with the uncontrolled system. Additionally, it is also found that the designed IT2NF controller is able to reduce the accelerations of the first and second floor by 64.8% and 54.6%, respectively. The proposed and designed control method reported in this study can be employed as an active vibration controller for multi-degree of freedom of flexible systems under the disturbances such as earthquake excitations.

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“…It is often used to compensate unstructured uncertainties in robot controller modeling. Fuzzy control [11] imitates human reasoning and decision-making processes on the basis of not depending on the precise mathematical model of the controlled object. Fuzzy logic is adopted in robot controllers to achieve good control performance under uncertain conditions.…”

Section: Introductionmentioning

confidence: 99%

Picking Robot Visual Servo Control Based on Modified Fuzzy Neural Network Sliding Mode Algorithms

Chen

Liu

et al. 2019

Electronics

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Through an analysis of the kinematics and dynamics relations between the target positioning of manipulator joint angles of an apple-picking robot, the sliding-mode control (SMC) method is introduced into robot servo control according to the characteristics of servo control. However, the biggest problem of the sliding-mode variable structure control is chattering, and the speed, inertia, acceleration, switching surface, and other factors are also considered when approaching the sliding die surface. Meanwhile, neural network has the characteristics of approaching non-linear function and not depending on the mechanism model of the system. Therefore, the fuzzy neural network control algorithm can effectively solve the chattering problem caused by the variable structure of the sliding mode and improve the dynamic and static performances of the control system. The comparison experiment is carried out through the application of the PID algorithm, the sliding mode control algorithm, and the improved fuzzy neural network sliding mode control algorithm on the picking robot system in the laboratory environment. The result verified that the intelligent algorithm can reduce the complexity of parameter adjustments and improve the control accuracy to a certain extent.

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Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

Cited by 10 publications

References 37 publications

Intelligent Tuning Control of two Link Flexible Manipulator with Piezoelectric Actuator

Intelligent Tuning Control of two Link Flexible Manipulator with Piezoelectric Actuator

A Novel Design of Interval Type-2 Neuro-Fuzzy Controller for Flexible Structure

Picking Robot Visual Servo Control Based on Modified Fuzzy Neural Network Sliding Mode Algorithms

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