In this paper, a learning-based method for estimating the parameters of the gravity term of a manipulator with the kernel trick approach is presented. This method extracts the mapping equation from the analytical form...
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ISBN:
(数字)9781728167947
ISBN:
(纸本)9781728167954
In this paper, a learning-based method for estimating the parameters of the gravity term of a manipulator with the kernel trick approach is presented. This method extracts the mapping equation from the analytical form of the dynamic equation. Based only on the configuration and sampling data of the robotic arm, Kernel ridge regression (KRR) and Support vector regression (SVR) algorithms are introduced to estimate the position parameters and provide a comparison between different learning regression techniques. The novelty of this work is the time-efficient estimation of robot gravity through randomly located joint sampling data using the kernel trick. The optimal solution to the optimal trade-off curve is proposed and discussed. Theoretical analysis shows that the joint angle and driving torque can be used to estimate the relationship between the center of gravity of the manipulator links and the mass of the connecting rod to obtain an accurate dynamic gravity model.
Approaches to helicopter UAV control often use the main and tail rotor thrusts, and the main rotor flapping angles as inputs. However, servomotors control the helicopter's four physical inputs which are the main r...
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ISBN:
(纸本)9781479908158
Approaches to helicopter UAV control often use the main and tail rotor thrusts, and the main rotor flapping angles as inputs. However, servomotors control the helicopter's four physical inputs which are the main rotor cyclic and collective pitch, and the tail rotor collective pitch. Helicopter models which treat the physical input are generally intractable for model-based control. We propose and identify a physical input model which is algebraically simple and therefore suitable for use in control design. The proposed model includes the vehicle's velocity to improve its accuracy.
Research in helicopter UAV control is inherently based on testing flight performance in the field. This paper extends preliminary flight test results previously published by the authors and provides a more thorough ex...
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ISBN:
(纸本)9781479908158
Research in helicopter UAV control is inherently based on testing flight performance in the field. This paper extends preliminary flight test results previously published by the authors and provides a more thorough experimental validation of the helicopter's motion control. A new input model, which includes velocity dependence in the main rotor thrust,is incorporated in the control. Experimental results for translational position control are presented using a number of reference trajectories.
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