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In this paper, a sensorless admittance control scheme is developed for robot manipulators in the presence of input saturation by employing neural networks. To deal with system uncertainties, the radial basis function neural network (RBFNN) is integrated into control design. In order to deal with input saturation, a compensator is applied to handle this problem. To interact with the environment, admittance...
The variable stiffness actuator (VSA) has been equipped on many new generations of robots because of its superior performance in terms of safety, robustness, and flexibility. However, the control of robots with joints driven by VSAs is challenging due to the inherited highly nonlinear dynamics. In this paper, a novel disturbance observer based adaptive neural network control is proposed for robotic...
The balance control a bipedal robot in the presence of external disturbances is still a challenge. In this paper, a novel optimal ankle stiffness regulation for humanoid robot balancing problem is proposed. The presented techniques are developed based on the integral reinforcement learning (IRL) algorithm, which is designed for unknown continuous-time systems using only partial knowledge of the system...
In this paper, the motion optimization for robotic manipulators is investigated by Support Area Level Set Algorithm (SALAS) through optimizing a high-dimensional nonlinear fitness function. The approach based on level set conception and the ability of Support Vector Machine(SVM) in distribution estimation integrates duel stages sampling strategies to avoid be converge in small search field too early...
Micro electromechanical system (MEMS) technologies, which have been widely used in robotics and automation, are being ported into medical embedded systems. A key change MEMS brings is the mechanic locomotion to physically move the embedded systems, which is usually actuated by a micro motor. However, classic motor driver and control cannot be used to drive the micro motor due to its tiny size and...
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