Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

Gaeid, Khalaf Salloum; Nashee, Asaad F; Ahmed, Ibrahim Abdulrab; Dekheel, Mohammed H.

doi:10.11591/eei.v10i1.2482

Cited by 8 publications

(5 citation statements)

References 15 publications

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“…As shown in Figure 2, the plant templates are drawn between open loop phase and open loop magnitude of the system for the frequencies starting from 0.1 to 1,000 rad/sec. These templates give the boundary of response for the various operating frequency range [27], [28].…”

Section: Plant Templatesmentioning

confidence: 99%

Quantitative feedback theory based robust speed control of vector controlled induction motor

Krishnankutty¹,

Thomas²,

Srivastava³

2023

Bulletin EEI

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In this research paper a method for the robust speed control of Indirect Field orient controlled induction motor (IM) is proposed. The quantitative feedback theory (QFT) in implemented to design the controller in order to achieve the desired performance for the closed loop system in the presence of uncertainties and parameter variations. In this research work the QFT based controller is designed for the simplified model of IM. The worst case of uncertainties and all possible parameter variations are taken into consideration. The IM with the controller developed is simulated using the MATLAB/Simulink and the results are analyzed and compared with the conventional proportional integral derivative (PID) controller. The time domain and frequency domain analysis of both controllers were conducted and compared. A study on the nature of electromagnetic torque and control signal is also included to justify the effectiveness of proposed controller. The simulation results verify the superior performance of the proposed robust control method compared to PID controller.

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Section: Plant Templatesmentioning

confidence: 99%

Quantitative feedback theory based robust speed control of vector controlled induction motor

Krishnankutty¹,

Thomas²,

Srivastava³

2023

Bulletin EEI

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“…The efficient picking of things by the robot requires an understanding of dynamics and kinematics [2]. Robot dynamics deals with joint force and torque, whereas kinematic analysis determines the position of the robot joints without taking force into account [3]. The kinematics and inverse kinematics of a 5 degrees of freedom (DOF) robotic arm are covered in this work.…”

Section: Introductionmentioning

confidence: 99%

“…Since closed-form solutions require precise initial values and converge more quickly than numerical ones, an algebraic approach was taken in this study to calculate joint angles. Gaeid et al [3] used Denavit-Hartenberg (DH) parameters and matrix transformation method to perform kinematic modeling of 6 DOF manipulator whereas Sutyasadi and Wicaksono [12] used hybrid controller of iterative learning and H∞ controller to control the robot joint for trajectory tracking applications. Quang et al [13] used radial basis function to derive the inverse dynamics of delta manipulator and Mashhadany [14] used adaptive neuro fuzzy inference system (ANFIS) controller and fractional order proportional, integral, derivative (FOPID) controller to obtain optimal trajectory for PUMA 560 manipulator.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling and kinematic analysis of 5 degrees of freedom serial link manipulator for online real-time pick and place applications

Singh

Kalaichelvi

Nagarasan

et al. 2023

IJECE

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<span lang="EN-US">Modeling and kinematic analysis are crucial jobs in robotics that entail identifying the position of the robot’s joints in order to accomplish particular tasks. This article uses an algebraic approach to model the kinematics of a serial link, 5 degrees of freedom (DOF) manipulator. The analytical method is compared to an optimization strategy known as sequential least squares programming (SLSQP). Using an Intel RealSense 3D camera, the colored object is picked up and placed using vision-based technology, and the pixel location of the object is translated into robot coordinates. The LOBOT LX15D serial bus servo controller was used to transmit these coordinates to the robotic arm. Python3 programming language was used throughout the entire analysis. The findings demonstrated that both analytical and optimized inverse kinematic solutions correctly identified colored objects and positioned them in their appropriate goal points.</span>

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“…Some researchers have developed low-cost robotic arm controller using a simple controller such as proportional integral (PI) controller [6], PID [7]- [9], fuzzy logic [10], [11], hybrid PID, and fuzzy [12], [13], optimal controller [14], neural network [15] and model-based controller [16]. A few researchers also tried to use robust control to control robotic arm joints such as sliding mode controller [17]- [20] and hybrid PIDsliding mode controller [21].…”

Section: Introductionmentioning

confidence: 99%

Robotic arm joint position control using iterative learning and mixed sensitivity H∞ robust controller

Sutyasadi

Wicaksono

2021

Bulletin EEI

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This paper proposes an improved control strategy of a robotic arm joint using hybrid controller consist of H∞ robust controller and iterative learning controller. The main advantage of this controller is the simple structure that made it possible to be implemented on a small embedded system for frugal innovation in industrial robotic arm development. Although it has a simple structure, it is a robust H∞ controller that has robust stability and robust performance. The iterative learning controller makes the trajectory tracking even better. To test the effectiveness of the proposed method, computer simulations using Matlab and hardware experiments were conducted. Variation of load was applied to both of the processes to present the uncertainties. The superiority of the proposed controller over the proportional integral derivative (PID) controller that usually being used in a low-cost robotic arm development is confirmed that it has better trajectory tracking. The error tracking along the slope of sinusoidal trajectory input was suppressed to zero. The biggest error along the trajectory that happened on every peak of the sinusoidal input, or when the direction is changed has been improved from 15 degrees to 4 degrees. This can be conceived that the proposed controller can be applied to control a low-cost robotic arm joint position which is applicable for small industries or educational purpose.

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Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

Cited by 8 publications

References 15 publications

Quantitative feedback theory based robust speed control of vector controlled induction motor

Quantitative feedback theory based robust speed control of vector controlled induction motor

Mathematical modeling and kinematic analysis of 5 degrees of freedom serial link manipulator for online real-time pick and place applications

Robotic arm joint position control using iterative learning and mixed sensitivity H∞ robust controller

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