Adaptive Control of a Two-Link Flexible Manipulator Using a Type-2 Neural Fuzzy System

Khan, Madad; Kara, Tolgay

doi:10.1007/s13369-020-04341-9

Cited by 9 publications

(10 citation statements)

References 44 publications

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“…Zhang, Zhang, Zhang and Dong [14] Planar TL FM; MC. Khan and Kara [15] Planar TL FM; MC. Pradhan and Subudhi [16] Planar TL FM; MC.…”

Section: Previous Work Limitations And/or Disadvantagesmentioning

confidence: 99%

“…Zhang, Zhang, Zhang and Dong [14] utilized a fuzzy proportional plus integral plus derivative control for the MC of a planar TL FM. Khan and Kara [15] used a neural fuzzy approach for the MC of a planar TL FM. Pradhan and Subudhi [16] used a self-tuning proportional plus integral plus derivative control for the MC of a planar TL FM.…”

Section: Introductionmentioning

confidence: 99%

“…SL FMs [1][2][3][4][5][6][7][8][9][10], planar FMs [1][2][3][4][5][6][7][8][9][11][12][13][14][15][16][17][18][19][20][21], joint space control [20,21], inverse dynamics techniques [18,20], and singular perturbation techniques [21] utilized for the development of control approaches in recent works have been summarized in the previous paragraphs.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Force and Motion Control of a Three-Dimensional Flexible Robot Considering Measurement Noises

2022

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This work addresses the end-effector trajectory-tracking force and motion control of a three-dimensional three-link robot considering measurement noises. The last two links of the manipulator are considered as structurally flexible. An absolute coordinate approach is used while obtaining the dynamic equations to avoid complex dynamic equations. In this approach, each link is modeled as if there is no connection between the links. Then, joint connections are expressed as constraint equations. After that, these constraint equations are used in dynamic equations to decrease the number of equations. Then, the resulting dynamic equations are transformed into a form which is suitable for controller design. Furthermore, the dynamic equations are divided as pseudostatic equilibrium and deviation equations. The control torques resulting from the pseudostatic equilibrium and the elastic deflections are obtained easily as the solution of algebraic equations. On the other hand, the control torques corresponding to the deviations are obtained without any linearization. Encoders, strain gauges, position sensors and force and moment sensors are required for measurements. Low pass filters are considered for the sensors. For the crossover frequencies of the sensors, low and high values are chosen to observe the filtering effect on the robot output.

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“…Zhang, Zhang, Zhang and Dong [14] Planar TL FM; MC. Khan and Kara [15] Planar TL FM; MC. Pradhan and Subudhi [16] Planar TL FM; MC.…”

Section: Previous Work Limitations And/or Disadvantagesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid Force and Motion Control of a Three-Dimensional Flexible Robot Considering Measurement Noises

2022

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“…The current trends show the use of sliding mode control and command shaping in vibration control of flexible manipulators. The performances of the control systems used for flexible manipulators were optimized using various optimization techniques like Genetic Algorithm, Particle Swarm Optimization, Vector Evaluated Particle Swarm Optimization (143) , Nelder-Mead Simplex Algorithm (144) , and Fuzzy Basis Function Network adaptive control algorithm (145) .…”

Section: Continued On Next Pagementioning

confidence: 99%

Dynamic modelling and control of flexible link manipulators: methods and scope- Part-1

Mishra¹,

Singh²

2021

IJST

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Objectives: This paper addresses two key issues in the area of flexible robotics. The issues are dynamic modelling and control of flexible link robots. A brief, yet, significant review is provided that addresses these issues. Methods: The various approaches used by researchers for dynamic modelling and control of flexible robots are presented. Besides that, methods used for achieving optimal control are also discussed. Findings: After a review of 153 research papers from the year 1975 to 2021, it has been found that a good dynamic model of flexible manipulator helps in reducing the control and computational efforts. Recent trends in research in the area of flexible manipulators are towards the use of sliding mode control and vision-based control techniques. Novelty: Inclusion of the effect of torsional vibrations besides lateral vibrations on the positional accuracy of flexible manipulators makes the current research work novel.

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“…To eliminate the drawbacks of model-based methods, model-free approaches for controlling robotic arms have been proposed. These controllers are mainly designed based on adaptive methods, fuzzy logic, or neural networks [4, 5, 6, 7, 8]. In ref.…”

Section: Introductionmentioning

confidence: 99%

FAT-based robust adaptive controller design for electrically direct-driven robots using Phillips q-Bernstein operators

2022

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This article proposes a robust and adaptive controller for industrial robot arms with multiple degrees of freedom without the need for velocity measurement. Many of the controllers designed for manipulators are model-based and require detailed knowledge of the system model. In contrast to these methods, this paper proposes a model-free controller using the Philips q-Bernstein operator as universal approximator. The designed controller can approximate uncertainties including external disturbances and unmodeled dynamics based on its universal approximation capability. Besides, most of the controllers revealed for robot arms are torque-based, which is not a realistic presumption from a practical point of view. In the proposed control method, the voltage applied to the actuator is considered as the control signal. However, unlike many voltage-based methods, the need to know the exact models of the system and the actuator has been eliminated in the presented method. Also, adaptive rules are extracted during the Lyapunov analysis to ensure system stability. Finally, to analyze the performance of the presented controller, this method is simulated for an industrial robot arm, and the results are analyzed. The proposed methodology is also compared to those of a strong state-of-the-art approximator, the Chebyshev neural network.

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Adaptive Control of a Two-Link Flexible Manipulator Using a Type-2 Neural Fuzzy System

Cited by 9 publications

References 44 publications

Hybrid Force and Motion Control of a Three-Dimensional Flexible Robot Considering Measurement Noises

Hybrid Force and Motion Control of a Three-Dimensional Flexible Robot Considering Measurement Noises

Dynamic modelling and control of flexible link manipulators: methods and scope- Part-1

FAT-based robust adaptive controller design for electrically direct-driven robots using Phillips q-Bernstein operators

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