01569nas a2200157   4500008004100000245008300041210006900124300001600193520099700209653002101206653001301227100001101240700001601251700001501267856012901282       2008                        eng d00aNeural network based robust adaptive control for a variable stiffness actuator0 aNeural network based robust adaptive control for a variable stif  a1028 - 10343 a<p>In this paper we present a robust adaptive controller based on a neural network (NN) for a variable stiffness actuator (VSA). The controller is able to independently set the mechanical stiffness and position at the joint shaft to guarantee robustness with respect to slowly time-varying and unmodeled friction coefficients affecting the dynamics of the actuator. The lumped uncertainties of the VSA including unmodeled dynamics are considered and approximated by a simple NN so that the controlled system is asymptotically stable, and remains effective while process conditions vary. To cope with the reconstruction error of the NN, a sliding mode like additional robust control term is introduced. The proofs for the uniformly ultimately bounded (UUB) and uniform asymptotic (UAS) stabilities for the closed-loop system are provided in detail via Lyapunov theory. Simulation and experimental results are reported in support of both validity and performance of the proposed approach.</p>
10aEmbedded Control10aRobotics1 aHuh, S1 aTonietti, G1 aBicchi, A.  uhttp://www.centropiaggio.unipi.it/publications/neural-network-based-robust-adaptive-control-variable-stiffness-actuator.html