Adaptive Robust Control for a Spatial Flexible Timoshenko Manipulator Subject to Input Dead-Zone

This paper presents an adaptive robust control algorithm for the nonlinear dynamics of robot manipulators with unknown backlash in gears. The basic nonlinear model of a serial manipulator robot is used for the controller design, and this is combined with the nonlinear proposed dead zone model, based on the input and output torque. The main idea of providing this model is to achieve a dynamic model of the system considering the backlash of the robot joint gears, and having less complexity such that the developed controller does not need the inverse backlash model. The adaptive robust controller is developed, without using the inverse backlash model. The proposed controller is designed based on an unknown dead zone parameter and it guarantees the stability and path tracking of the robot trajectory with unknown dead zone parameter in the desired range. Numerical simulations are conducted to show the effectiveness of the proposed controller. Finally, the efficiency and capability of the proposed controller in dealing with the unknown backlash nonlinearities in gears of the manipulator are demonstrated by experimental results with a five-bar manipulator.

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Decentralised adaptive robust control schemes of uncertain large-scale time-delay systems with multiple unknown dead-zone inputs

IET Control Theory and Applications ◽

10.1049/iet-cta.2016.1277 ◽

2017 ◽

Vol 11 (9) ◽

pp. 1360-1370 ◽

Cited By ~ 13

Author(s):

Hansheng Wu

Keyword(s):

Time Delay ◽

Robust Control ◽

Large Scale ◽

Dead Zone ◽

Adaptive Robust Control ◽

Delay Systems ◽

Time Delay Systems ◽

Control Schemes

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Optimal Design of Adaptive Robust Control for the Delta Robot with Uncertainty: Fuzzy Set-Based Approach

Applied Sciences ◽

10.3390/app10103472 ◽

2020 ◽

Vol 10 (10) ◽

pp. 3472 ◽

Cited By ~ 2

Author(s):

Linlin Wu ◽

Ruiying Zhao ◽

Yuyu Li ◽

Ye-Hwa Chen

Keyword(s):

Optimal Control ◽

Robust Control ◽

Optimal Design ◽

Fuzzy Set ◽

Dead Zone ◽

Adaptive Robust Control ◽

Fast Time ◽

Theoretic Approach ◽

Adaptation Mechanism ◽

Delta Robot

An optimal control design for the uncertain Delta robot is proposed in the paper. The uncertain factors of the Delta robot include the unknown dynamic parameters, the residual vibration disturbances and the nonlinear joints friction, which are (possibly fast) time-varying and bounded. A fuzzy set theoretic approach is creatively used to describe the system uncertainty. With the fuzzily depicted uncertainty, an adaptive robust control, based on the fuzzy dynamic model, is established. It designs an adaptation mechanism, consisting of the leakage term and the dead-zone, to estimate the uncertainty information. An optimal design is constructed for the Delta robot and solved by minimizing a fuzzy set-based performance index. Unlike the traditional fuzzy control methods (if-then rules-based), the proposed control scheme is deterministic and fuzzily optimized. It is proven that the global solution in the closed form for this optimal design always exists and is unique. This research provides the Delta parallel robot a novel optimal control to guarantee the system performance regardless of the uncertainty. The effectiveness of the proposed control is illustrated by a series of simulation experiments. The results reveal that the further applications in other robots are feasible.

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