Tracking Control and Reference Trajectory Generation in a LOM System

Liu, Y.; Li, C.; Wang, D.; Guo, Xiaojun

doi:10.1007/s00170-002-1376-1

Cited by 4 publications

(2 citation statements)

References 11 publications

(9 reference statements)

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“…Tracking control of the machines to achieve precision positioning with minimum errors has been an attractive field of study for the researchers. Digital control algorithms including crosscoupled control [12], zero-phase error tracking control [13] and precision tracking control [14] are widely utilized in designing tracking controllers in high-speed motion machines [15][16][17]. In this study, a precision tracking controller is designed.…”

Section: Design Of a Precision Tracking Controllermentioning

confidence: 99%

Precision tracking control of a horizontal arm coordinate measuring machine in the presence of dynamic flexibilities

Özel

2004

Int J Adv Manuf Technol

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One of the major sources that affect measurement accuracy and limit the use of high motion speeds in coordinate measuring machines (CMM) is the position error. In fact, static and dynamic probe errors are more direct factors in measuring machine accuracy, but are not the subject of this research. However the accuracy of acquisition of component position errors using a CMM in motion is also of importance, hence the dynamics of a CMM need to be considered. Therefore, this research aims to model the dynamics of a horizontal arm CMM by considering drive flexibility at joints and evaluates the characteristics of the system for fine motion control purposes. Design of a precision tracking controller (PTC) to perform superior tracking for enhancing the measurement accuracy and the probing speed in providing less inspection time at high motion speeds is carried out. A dynamic model for the CMM is developed including drive flexibilities represented with lumped springs at the joints. Due to the non-collocated nature of the control scheme in the flexible CMM dynamics, a non-minimum phase system is observed in the proposed CMM model. Using the derived CMM model with joint flexibilities, tracking motion control simulations are conducted at different probing speeds for the cases where a PI controller and a feedback PTC are employed. A comparison of the PI controller with the feedback PTC is also performed. Results demonstrate that the effects of joint flexibilities on the contour error and probing speeds are significant and the PI controller is not capable of providing good accuracy during challenging tasks such as corner tracking. However, the simulation results indicated that by using the proposed feedback precision tracking controller, contour errors in corner tracking that are caused by joint flexibilities can be reduced effectively.T. Özel

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Section: Design Of a Precision Tracking Controllermentioning

confidence: 99%

Precision tracking control of a horizontal arm coordinate measuring machine in the presence of dynamic flexibilities

Özel

2004

Int J Adv Manuf Technol

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“…Based on this control strategy, the control systems with multiple axes are coupled into a multivariable control system. Up to the present, the cross-coupled control principle [2][3][4][5] has been used to treat a multi-axis system as a whole unit and calculate the control action for the servomechanism by considering the skew error of all synchronizing axes. The objective of this study is, based on this concept, to calculate the control action for the servomechanisms by considering the skew error of all synchronizing axes.…”

Section: Introductionmentioning

confidence: 99%

Robust Neural Network Controller Design For A Biaxial Servo System

Yu¹,

Chen²

2007

Asian Journal of Control

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A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new neural network based cross‐coupled control and neural network techniques are used together to cancel out the skew error. In the proposed control scheme, the conventional fixed gain PID cross‐coupled controller (PIDCCC) is replaced with the neural network cross‐coupled controller (NNCCC) to maintain biaxial servo system synchronization motion. In addition, neural network PID position velocity and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. This scheme provides strong robustness with respect to uncertain dynamics and nonlinearities. The simulation results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

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