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- W2732983487 abstract "This paper presents a neural control technique to study the balancing of a base-excited inverted pendulum. The pendulum has two degrees of rotational freedom and the base-point moves freely in three-dimensional space. The goal is to apply control torques to keep the pendulum in a prescribed position in spite of disturbing base-point movements. The inclusion of base-point motion leads to a non-autonomous dynamic system with time-varying parametric excitation, which makes the control task challenging. Neural networks are used here, for on-line estimations of the pendulum's base-point movements, using only measurable variables. These estimates are then utilized within the feedforward portion of a controller to produce compensating signals. A neural inverse modeling approach is used for off-line training the appropriate networks. The examination of the proposed control system, through simulations, exhibits positive aspects, which cannot be achieved by the previously developed technique, based on Lyapunov stability analyses. These aspects include fast, yet well-maintained damped, responses with reasonable control torques. The work presented here, can benefit practical problems such as the study of stable locomotion of the human upper body or of bipedal robots." @default.
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- W2732983487 date "1999-07-01" @default.
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- W2732983487 title "Control of base-excited inverted pendulums using a neural inverse modeling approach" @default.
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- W2732983487 doi "https://doi.org/10.1016/s1474-6670(17)56870-6" @default.
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