Robust Compliant Motion Control of Robot With Nonlinear Friction Using Time-Delay Estimation

Jin, Maolin; Kang, Sang Hoon; Chang, Pyung Hun

doi:10.1109/tie.2007.906132

Cited by 209 publications

(122 citation statements)

References 34 publications

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“…We developed a controller that compensates for the uncertainties and complex dynamics through the implementation of TDE. [21][22][23][24] To formulate the TDE controller, we rewrite Equation (1) with only the magnetic force on one side, and substitute the acceleration with the second time derivative of the position vector, i.e.,…”

Section: Dynamic Modelling and Controlmentioning

confidence: 99%

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Electromagnetic Steering of a Magnetic Cylindrical Microrobot Using Optical Feedback Closed-Loop Control

Ghanbari

Chang

Nelson

et al. 2014

International Journal of Optomechatronics

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Control of small magnetic machines in viscous fluids may enable new medical applications of microrobots. Small-scale viscous environments lead to low Reynolds numbers, and although the flow is linear and steady, the magnetic actuation introduces a dynamic response that is nonlinear. We account for these nonlinearities, and the uncertainties in the dynamic and magnetic properties of the microrobot, by using time-delay estimation. The microrobot consists of a cylindrical magnet, 1 mm long and 500 lm in diameter, and is tracked using a visual feedback system. The microrobot was placed in silicone oil with a dynamic viscosity of 1 Pa.s, and followed step inputs with rise times of 0.45 s, 0.51 s, and 1.77 s, and overshoots of 37.5%, 33.3%, and 34.4% in the x, y, and z directions, respectively. In silicone oil with a viscosity of 3 Pa.s, the rise times were 1.04 s, 0.72 s, and 2.19 s, and the overshoots were 47.8%, 48.5%, and 86.8%. This demonstrates that closed-loop control of the magnetic microrobot was better in the less viscous fluid.

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Section: Dynamic Modelling and Controlmentioning

confidence: 99%

“…One may start with m close to or slightly less than the mass of the microrobot, and vary it to tune the controller performance (further details on this are given by Ref. [22] ). The controller was set to follow a step input with components in the x, y, and z directions.…”

mentioning

confidence: 99%

Electromagnetic Steering of a Magnetic Cylindrical Microrobot Using Optical Feedback Closed-Loop Control

Ghanbari

Chang

Nelson

et al. 2014

International Journal of Optomechatronics

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“…Particularly, it has been also implemented for robot manipulators to perform trajectory tracking control, force control, impedance control, and dual arm cooperative control [17][18][19][20][21]. The TDC for robot manipulators consists of two elements [9,10]: the robot dynamics canceling element using the TDE, and the desired error dynamics injecting element.…”

Section: Introductionmentioning

confidence: 99%

“…Mostly, the TDE is computed from one-sample time delayed information. The TDE functions perfectly for continuous nonlinearities (such as gravity, Coriolis and centrifugal torques, viscous friction, disturbance) in robot dynamics, however, pulse type TDE error occurs for estimation of discontinuous nonlinearities such as Coulomb friction and Stiction [19,22]. The performance of the closed-loop systems are greatly affected by the TDE error.…”

Section: Introductionmentioning

confidence: 99%

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Bae¹,

Jin²,

Suh³

et al. 2017

Journal of Electrical Engineering and Technology

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-A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMAtype robot manipulator.

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“…1) In particular, the TDC scheme is known as a robust nonlinear control scheme for model uncertainties and displays positive performance for the trajectory tracking problem. 2,3) Several previous studies on longitudinal auto-landing control are well summarized by Ju and Tsai 4) who implemented an adaptive backstepping control scheme. Backstepping control is based on Lyapunov Stability and requires strict feedback equation forms of the system's dynamic model, which can be quite complicated for developing control law.…”

Section: Introductionmentioning

confidence: 99%

Aircraft Longitudinal Auto-landing Guidance Law Using Time Delay Control Scheme

Choi

Lee

Kim

et al. 2010

Trans. Japan Soc. Aero. S Sci.

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The objective of this paper is applying the Time Delay Control scheme for the aircraft auto-landing guidance problem. A stability and control augmentation system and longitudinal auto-landing guidance law, using Time Delay Control, is proposed and evaluated through a simulation with model uncertainties and wind disturbances. The proposed Time Delay Control guidance law shows good performance and is robust to model uncertainties and disturbances.

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Robust Compliant Motion Control of Robot With Nonlinear Friction Using Time-Delay Estimation

Cited by 209 publications

References 34 publications

Electromagnetic Steering of a Magnetic Cylindrical Microrobot Using Optical Feedback Closed-Loop Control

Electromagnetic Steering of a Magnetic Cylindrical Microrobot Using Optical Feedback Closed-Loop Control

Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

Aircraft Longitudinal Auto-landing Guidance Law Using Time Delay Control Scheme

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