List of Titles

Authors: Van Nguyen, Thien , Le, Hai , Tran, Hoang , Nguyen, Duc , Nguyen, Minh , Nguyen, Linh
Date: 2021
Type: Text , Conference paper
Relation: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2021, 28 April 2021 through 29 April 2021 p. 111-116
Full Text: false
Reviewed:
Description: The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic two-wheel robot where the obtained results demonstrate its effectiveness. © 2021 IEEE.

Authors: Van Nguyen, Thien , Le, Hai , Tran, Hoang , Nguyen, Duc , Nguyen, Minh , Nguyen, Linh
Date: 2021
Type: Text , Conference paper
Relation: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2021 p. 85-90
Full Text: false
Reviewed:
Description: The paper addresses the problem of efficiently controlling a class of single input multiple output (SIMO) under-Actuated robotic systems such as a two dimensional inverted pendulum cart or a two dimensional overhead crane. It is first proposed to employ the hierarchical sliding mode control approach to design a control law, which guarantees stability and anti-swing of the vehicle when it is driven on a predefined trajectory. More importantly, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by the proposed fuzzy logic mechanism, which results in the efficient operation of the SIMO under-Actuated system in real time. The proposed algorithm was then implemented in the synthetic environment, where the obtained results demonstrate its effectiveness. © 2021 IEEE.

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