Adaptive dynamic fuzzy neural network-based decoupled sliding-mode controller with hybrid sliding surfaces
by Guoliang Zhao; Hongxing Li; Zhankui Song
International Journal of Automation and Control (IJAAC), Vol. 7, No. 3, 2013

Abstract: The main motivation for this study is to remove the constraint of known non-linear dynamics in the control law, and eliminate the chattering in the switching. Thus, the dynamic fuzzy neural network (DFNN) is applied to better approximate the unknown non-linear dynamics in a decoupled sliding mode control (DSMC) problem for a class of fourth-order non-linear systems. To avoid the drawback of control chattering occurring in the sliding mode, a fractional order PI compensator is used to compensate for disturbance forces while suppressing chattering effect. Using this approach, the response of the system will converge faster than that of previous reports. Finally, simulations adopting this framework are presented for cart-pendulum system and TORA system. Simulation results show the effectiveness of the newly proposed adaptive DFNN-based decoupled sliding mode control method.

Online publication date: Sat, 12-Jul-2014

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