Inverse dynamics and control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator

Singh, Yogesh; Vinoth, V.; Kiran, Y. Ravi; Mohan, Santhakumar

doi:10.1016/j.rcim.2015.02.007

Cited by 46 publications

(26 citation statements)

References 44 publications

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“…Analysis results reveal that this manipulator has the advantages of a void-free workspace with a convex type of borderline and a closed type of direct kinematics. For the U-shape 3-PPR PPM [15], the motion control with disturbance observer is proposed and validated. Here, the manipulator can perform as a motion table in the range of meso (between micro-and milli-metre levels), and it can be used for applications, providing accurate positioning and trajectory capabilities to the end-effector, especially for milling and other machining processes.…”

Section: Performance Evaluation Of the Non-redundant Ppmsmentioning

confidence: 99%

“…For the 3-PPR PPMs, extensive research has been reported in [13][14][15][16][17]. Kinematic analysis and optimal design of a 3-PPR PPM with a ∆-shape (equilateral triangle) base platform were presented in [13].…”

Section: Introductionmentioning

confidence: 99%

“…In order to maximize the manipulator's workspace, a 3-PPR PPM with a U-shape (square) base platform was introduced in [14]. The dynamics and controller performance of the U-shape 3-PPR PPM was investigated in [15]. 3-PPR PPMs with ∆and U-shape base platforms were compared with respect to kinematic sensitivity to joint clearances and workspace in [16].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance Analysis and Optimum Design of a Redundant Planar Parallel Manipulator

2019

Symmetry

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This work presents a comprehensive performance evaluation and optimum design of a novel symmetrical 4-PPR (P indicates the prismatic joint, R denotes the revolute joint, and the letter with underline represents an active joint) redundant planar parallel manipulator. The kinematic model is established, upon which the inverse position and singularity are analyzed. Based on the evaluation of dexterity, velocity, and stiffness performance, the optimum region is achieved. With the optical design parameters, a case study for the analysis of dynamic behavior is conducted. Performance comparison between the redundant manipulator and another two non-redundant 3-PPR planar parallel manipulators, one with a Δ-shape symmetrical structure and the other with U-shape symmetrical structure, is presented. Simulation results reveal that the U-shape manipulator has the greatest velocity performance. Moreover, the redundant manipulator possesses the best dexterity, stiffness, and dynamic performance.

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Section: Performance Evaluation Of the Non-redundant Ppmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance Analysis and Optimum Design of a Redundant Planar Parallel Manipulator

2019

Symmetry

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“…In order to control the challenging dynamics of the robots, the nonlinearity in the dynamics must be turned into linearity via using techniques such as inverse dynamics. Afterwards, by choosing an appropriate controller, such as PD control, it is feasible to control the challenging dynamics with high precision [19,20,[26][27][28][29][30]. A proper controller not only provides a superior performance in tracking the desired trajectory but also diminishes the negative effects of disturbances, the clearance of joints, and the elasticity of the links or joints.…”

Section: Introductionmentioning

confidence: 99%

Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm Optimization

Mahmoodabadi

Ziaei

2019

Journal of Robotics

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This paper endeavors to contribute to the field of optimal control via presenting an optimal fuzzy Proportional Derivative (PD) controller for a RPP (Revolute-Prismatic-Prismatic) robot manipulator based on particle swarm optimization and inverse dynamics. The Denavit-Hartenberg approach and the Jacobi method for each of the arms of the robot are employed in order to gain the kinematic equations of the manipulator. Furthermore, the Lagrange method is utilized to obtain the dynamic equations of motion. Hence, in order to control the dynamics of the robot manipulator, inverse dynamics and a fuzzy PD controller optimized via particle swarm optimization are used in this research study. The obtained results of the optimal fuzzy PD controller based on the inverse dynamics are compared to the outcomes of the PD controller, and it is illustrated that the optimal fuzzy PD controller shows better controlling performance in comparison with other controllers.

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“…Kiran et. all performed inverse dynamics of three degrees of freedom (DOF) U-shaped planar parallel manipulator having three legs consisting of prismatic-prismatic-revolute (PPR) joint arrangement in which each leg has one active prismatic joint [30]. Jiang, Li and Wang proposed a novel planar 2-DOF parallel kinematic machine with kinematic redundancy and presented a method for redundant force optimization is presented to improve the precision of the machine.…”

mentioning

confidence: 99%

Lagrangian Dynamics Analysis of a XY-Theta Parallel Robotic Machine Tool

Enferadi

Tavakolian

2017

Period. Polytech. Mech. Eng.

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Inverse dynamics and control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator

Cited by 46 publications

References 44 publications

Performance Analysis and Optimum Design of a Redundant Planar Parallel Manipulator

Performance Analysis and Optimum Design of a Redundant Planar Parallel Manipulator

Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm Optimization

Lagrangian Dynamics Analysis of a XY-Theta Parallel Robotic Machine Tool

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