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RISSThis paper concerned about enhanced feedback error learning control (EFELC) strategy for and n-degree-of-freedom robotic manipulator. It covers the design and simulation study of the neural-network-based controller for the manipulator with a view of ...
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RISS 인기검색어
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다국어 초록 (Multilingual Abstract)
This paper concerned about enhanced feedback error learning control (EFELC) strategy for and n-degree-of-freedom robotic manipulator. It covers the design and simulation study of the neural-network-based controller for the manipulator with a view of tracking a predetermined trajectory of motion in the joint space.
One Robot was simulated as a three-axis manipulator with the dynamics of the tool (fourth link) neglected and the mass of the load incorporated into the mass of the third link.
For simplicity, only the first two joints of the manipulator were considered in the simulation study. The overall performance of the control system under different conditions, namely, trajectory tracking, variations in trajectory, and different initial weight values were studied and comparison made with the existing feedback error learning control(FELC) strategy.
One Robot was simulated as a three-axis manipulator with the dynamics of the tool (fourth link) neglected and the mass of the load incorporated into the mass of the third link.
For simplicity, only the first two joints of the manipulator were considered in the simulation study. The overall performance of the control system under different conditions, namely, trajectory tracking, variations in trajectory, and different initial weight values were studied and comparison made with the existing feedback error learning control(FELC) strategy.
This paper concerned about enhanced feedback error learning control (EFELC) strategy for and n-degree-of-freedom robotic manipulator. It covers the design and simulation study of the neural-network-based controller for the manipulator with a view of tracking a predetermined trajectory of motion in the joint space.
One Robot was simulated as a three-axis manipulator with the dynamics of the tool (fourth link) neglected and the mass of the load incorporated into the mass of the third link.
For simplicity, only the first two joints of the manipulator were considered in the simulation study. The overall performance of the control system under different conditions, namely, trajectory tracking, variations in trajectory, and different initial weight values were studied and comparison made with the existing feedback error learning control(FELC) strategy.
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