Variable impedance control based on barrier Lyapunov function for constrained human-robot interaction
Impedance control is a compliant control method widely used in human-robot interaction(HRI).It regulates the tracking accuracy of the robot and the contact compliance with the environment.However,fixed impedance pa-rameters limit the applicability of impedance control in complex HRI tasks.In order to realize the role switching be-tween leader and follower in HRI,a variable impedance control approach is proposed based on barrier Lyapunov function(BLF)for constrained HRI.Firstly,A novel impedance model is established and the impedance parame-ters are designed as the control input of the new impedance system.The design problem of variable impedance con-troller with impedance constraints is transformed into a quadratic programming problem.Secondly,BLF-based adaptive neural network constrained controller is designed to solve the tracking control problem.At the same time,the controller ensures that the error signal within the constrained domain.The radial basis neural networks(NNs)are adopted to handle uncertainty of the robot dynamics and guarantee tracking performance.The stability of the closed-loop system is proved by the Lyapunov stability theorem.Finally,the effectiveness of the proposed method is verified by two simulation cases.
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