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A robust adaptive control approach is proposed to solve the consensus problem of multiagent systems. Compared with the previous work, the agent's dynamics includes the uncertainties and external disturbances, which is more practical in real-world applications. Due to the approximation capability of neural networks, the uncertain dynamics is compensated by the adaptive neural network scheme. The effects...
An adaptive control approach is proposed to deal with the multi-manipulator leader-follower control based on the multi-agent theory. In the current multi-agent literature, agents are assumed to have determined linear models. However, the real manipulatorpsilas dynamics is highly nonlinear and contains uncertain parameters. According to the ldquoinearity-in-parametersrdquo property, the adaptive updating...
An adaptive control approach is proposed to deal with the multi-manipulator system consensus problem based on the multi-agent theory. In the current multi-agent literature, agents are assumed to have determined models. However, the real manipulator's dynamics contains uncertain parameters. According to the ldquolinearity-in-parametersrdquo property, the adaptive updating law for uncertain dynamics...
An adaptive control approach is proposed to deal with the multiple manipulators consensus problem based on the multi-agent theory. In the current multi-agent literature, agents were assumed to have determined models. However, the practical manipulator's kinematics contains uncertain parameters. By using the projection method, the adaptive updating law for uncertain kinematic parameters is derived...
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