A nov el class of hysteresis mo dels w as proposed. A cer tain num ber o f different deadband w idth backlash models are superposed, w hich represents a dynamics to m i c hysteresis in the actuator. With the mo del proposed, an radial basis function neural netw ork ( RBFN )-based adaptive control scheme for nonlinear sy stems w ith unknow n hysteresis nonlinearity w as dev elo ped. The control scheme adopts the de- sign method of pseudo-co ntro l. Witho ut the assumption of boundedness of disturbance term , it is tuned thr oug h adaptive algo rithm . The stability is rigidly pr oved v ia Lyapunov theory and the effectiveness of the pro posed contr ol scheme is illustrated through simulatio n.

Adaptive Hysteresis.pdf

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