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Adaptive neural control for a class of nonlinear systems with uncertain hysteresis inputs and time-varying state
Beibei Ren1, Shuzhi Sam Ge, Tong Heng Lee
1Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore. renbeibei@nus.edu.sg
Abstract:
In this paper, adaptive variable structure neural control is investigated for a class of nonlinear systems under the effects of time-varying state delays and uncertain hysteresis inputs. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design, and the effect of the uncertain hysteresis with the Prandtl-Ishlinskii (PI) model representation is also mitigated using the proposed control. By utilizing the integral-type Lyapunov function, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded (SGUUB). Extensive simulation results demonstrate the effectiveness of the proposed approach.
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