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Go to Editorial ManagerIn this paper, a second order Sliding Mode Controller (SMC), based on Super – Twisting algorithm, Fuzzy estimator and PID controller is presented for quarter vehicle active suspensions. Because of the chattering that appeared at the output of the system when using first order SMC, second order SMC is preferred. The proposed controller has been derived in order to achieve the convergence and the stability of the system that can improve the comfortable driving and vehicles safety against different road disturbances. The Artificial Bee Colony optimization method has been utilized to find the optimal values of the proposed controller parameters. The obtained results of the simulations have been verified the efficiency and the ability of the proposed control scheme to suppress the oscillations and give the stability of the suspension system in the presence of uncertainty and different road disturbances.
In this paper, a neuro-fuzzy network-based adaptive tracking controller is suggested for controlling a type of nonlinear system. Where two neuro-fuzzy networks have been used to learn the system dynamics uncertainty bounds by using Lyapunov method. Then the output of these two networks are used to build a sliding mode controller. The stability of the control system is proved and stable neuro-fuzzy controller parameters adjustment laws are selected using Lyapunov theory. Simulation case study shows that the controlled system tracking the reference model effectively with smooth control effort and robust performance has been achieved.