Trajectory tracking controller of the hybrid robot for milling

Petko, Maciej; Karpiel, Grzegorz; Gac, Konrad; Góra, Grzegorz; Kobus, Konrad; Ochoński, Janusz

doi:10.1016/j.mechatronics.2016.03.012

Cited by 20 publications

(8 citation statements)

References 10 publications

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“…Possition and orientation of the tool frame O E x E y E z E with repect to the coordinate frame of the end-effector are determined by the general coordinates 6 x E , 6 y E , 6 z E , 6 α E , 6 β E , 6 η E , and represented by matrix 6 Considering the kinematic chain:…”

Section: Kinematic Equations Of the Robotmentioning

confidence: 99%

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Inverse dynamic analysis of milling machining robot, application in calibration of cutting force

Thanh¹

2019

JST

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This article presents analysis of inverse dynamics of a serial manipulator in milling process. With the exception of positioning accuracy issue, machining by robots have more advantages than by conventional CNC milling machines, due to higher flexible kinematics (many links and degrees of freedom) and larger working space. Therefore, motion of the robot links is more complicated. Process forces and complicated motion involve to difficulties in solving dynamic problems of robots. This affects the robot control to match machining requirements. This article utilizes the transformation coordinates and the homogeneous transformation matrices to analysis of kinematics and dynamics of the robot. In general, cutting forces are determined by using empirical formulas that lead to errors of cutting force values. Moreover, the cutting forces are changing and causing vibration during machining process. Errors of cutting force values affect the accuracy of the dynamic model. This paper proposes an algorithm to compute the cutting forces based on the feedback values of the robot's motion. The results of kinematic and dynamic simulation of the computing program and calibrating cutting force prove intuitively and reliably validation of the proposed method.

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Section: Kinematic Equations Of the Robotmentioning

confidence: 99%

“…Beside the advantages, there are difficulties and challenges that being addressed to use robots for machining tasks [2,6]. Firstly, due to a large number of links, motion of the last link 774 or the end-effector is a combination motion of the privious links.…”

Section: Introductionmentioning

confidence: 99%

Inverse dynamic analysis of milling machining robot, application in calibration of cutting force

Thanh¹

2019

JST

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“…In the literature [6], a simplified dynamic model is taken as the consideration and it is verified that the control scheme designed for the trajectory tracking based on the robot reduced model could improve the trajectory tracking accuracy. In the literature [7], a five degree of freedom hybrid robot model predictive trajectory tracking controller for milling is designed, and the control law of calculating torque is planned to improve the performance of trajectory tracking. In the literature [8], a novel hybrid humanoid robot arm is the controlled object, an sliding mode controller based on the adaptive backstepping approach is introduced under considering the parameter uncertainties and disturbances, and finally the superiority of the trajectory tracking controller is verified by experiments.…”

Section: Introductionmentioning

confidence: 99%

Par4 Parallel Robot Trajectory Tracking Control Based on DMR-GWO2 and Fuzzy Predictive

Zhang¹,

Ming²

2021

IJCIS

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A dynamic Grey Wolf Optimizer (GWO) is proposed, noted as DGWO2, and a novel dynamic improved GWO algorithm is obtained after transferring the mutation operator and the eliminating-reconstructing mechanism to the DGWO2, noted as DMR-GWO2. A Type-2 fuzzy predictive compensation PID trajectory tracking controller based on the DMR-GWO2 is proposed to attain the tracking targets for the trajectory control of Par4 parallel robot. In the trajectory tracking controller, the DMR-GWO2 is designed for optimizing the Type-2 fuzzy logic controller which is in parallel with the PID controller to speed up the response of the parallel robot and to get the high adaptive capacity of the whole system. One input of the Type-2 fuzzy logic controller is the tracking error, while the other input is the sum of the derivative of the tracking error and the change rate of the expected angle. Finally, the experiments verify the effectiveness of the designed trajectory tracking controller and the tracking errors are small.

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“…In recent years, tremendous work has been carried out on the design and development of 5-axis hybrid robots having A/C type wrist, the Tricept, the Exechon and the TriMule for example. The relevant work primarily focuses on type synthesis [4,17,18], kinetostatic analysis [19][20], kinematic optimization [21][22][23][24][25][26][27], and CNC controller development [28][29][30], etc. Unfortunately, little attention has been paid to non-singular tool path planning though singularity problem can be avoided, to some extent, by placing such a robot a tilt angle with respect to the workpiece frame at the cost of reducing the useful workspace envelop [23,31].…”

Section: Introductionmentioning

confidence: 99%

Inverse kinematics of a 5-axis hybrid robot with non-singular tool path generation

Liu

Huang

2019

Robotics and Computer-Integrated Manufacturing

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Trajectory tracking controller of the hybrid robot for milling

Cited by 20 publications

References 10 publications

Inverse dynamic analysis of milling machining robot, application in calibration of cutting force

Inverse dynamic analysis of milling machining robot, application in calibration of cutting force

Par4 Parallel Robot Trajectory Tracking Control Based on DMR-GWO2 and Fuzzy Predictive

Inverse kinematics of a 5-axis hybrid robot with non-singular tool path generation

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