In the new era of China, with the improvement of people's level day by day, people's awareness of animal protection is gradually enhanced. However, the lack of operator experience of the breeder will cause the...
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In this modern world, we are naturally dependent on technology, which is constantly evolving. At the same time, our fear of data fraud is increasing every day. The ever-increasing number of attacks on our servers indi...
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This paper explores the integration of virtual reality (VR) with teleoperation systems to enhance human-robot interaction. With the rise of remote operations, traditional methods often rely on two-dimensional interfac...
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Three degree of freedom (DOF) parallel mechanisms (PM) are widely used in light industry, medical industry, agriculture, aerospace and other fields because of their excellent motion performance and cost performance. A...
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3-axis force sensors for both normal and shear force sensing have a promising prospect in the field of robotic applications. In this article, a novel flexible 3-axis force sensor was fabricated. The sensor is featured...
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Electric vehicles (EVs) have gained immense popularity in recent times owing to the decrease in conventional energy resource reserves and the concurrent threat to the environment caused from the harmful discharge of I...
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The marine lifting arm system is a novel type of lifting equipment for the dismantling of large offshore platforms. In practical application, the marine lifting arm system is commonly subject to unexpected disturbance...
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ISBN:
(纸本)9789819607976;9789819607983
The marine lifting arm system is a novel type of lifting equipment for the dismantling of large offshore platforms. In practical application, the marine lifting arm system is commonly subject to unexpected disturbances such as persistent vessel-induced disturbances, uncertain dynamics, and physical constraints, posing significant challenges for controller system design. This paper proposes a neural network (NN) based adaptive tracking control method with state constraints for the marine lifting arm system to effectively compensate for vessel motions induced by wave disturbances. First, the dynamic model of a marine lifting system is established by employing Lagrange's method. Subsequently, a nonlinear controller is developed based on the dynamic model to compensate for 3-DOF vessel motions, including heave, roll, and pitch motion. By constructing constrained terms, the nonlinear controller effectively restricts the lifting arm's motion within the predefined range, ensuring the safety of lifting operations even under adverse sea conditions. The neural network is employed to estimate parameter/structure uncertainties and the nonlinear input dead zones for lifting arm systems. In particular, the designed update law of the neural network considers physical constraints, thereby further ensuring that the lifting arm operates within the safe range. The theoretical stability of the proposed control system is rigorously proven using the Lyapunov technique. Finally, the practicality and effectiveness of the proposed method are verified by the hardware experiments on a self-built offshore lifting system.
This study aims to design and optimize a motor-driven frog-like jumping robot leg for efficient vertical jumps and multiple consecutive horizontal jumps. We have conducted bionic research on frog legs' structure a...
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In the realm of advanced cognitive processes, animals employ both egocentric and allocentric reference frames for navigation. While prior studies have largely concentrated on differentiating and transitioning between ...
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The spreading of mobile communication networks resulted in a vast amount of signaling traffic on the control plane. It is quite challenging to analyze the extensive number of message sequences, recognize patterns and ...
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