Abstract
In this paper, a neuro-fuzzy fast terminal sliding mode control method is proposed for controlling a class of nonlinear systems with bounded uncertainties and disturbances. In this method, a nonlinear terminal sliding surface is firstly designed. Then, this sliding surface is considered as input for an adaptive neuro-fuzzy inference system which is the main controller. A proportinal-integral-derivative controller is also used to asist the neuro-fuzzy controller in order to improve the performance of the system at the begining stage of control operation. In addition, bee algorithm is used in this paper to update the weights of neuro-fuzzy system as well as the parameters of the proportinal-integral-derivative controller. The proposed control scheme is simulated for vibration control in a model of atomic force microscope system and the results are compared with conventional sliding mode controllers. The simulation results show that the chattering effect in the proposed controller is decreased in comparison with the sliding mode and the terminal sliding mode controllers. Also, the method provides the advantages of fast convergence and low model dependency compared to the conventional methods.
Highlights
Nonlinear control methods have significantly developed in terms of theory and practice
As can be seen from this figure, the results reveal less chattering compared with Sliding Mode Controller (SMC) and Terminal SMC (TSMC), but the tracking performance is getting worse
A Neuro-Fuzzy FTSMC (NFFTSMC) method has been proposed for a class of nonlinear systems to remove the chattering effect, to have finite-time asymptotic convergence, and to reduce fuzzy rules
Summary
Nonlinear control methods have significantly developed in terms of theory and practice. The conventional sliding mode control method has combined with ANFIS in [3235] These adaptive FSMC methods have the advantages of robustness and stability of the SMC, the model-free feature of fuzzy systems, and the learning capability of ANFIS. In such hybrid configurations, the common sliding surface is a linear surface which only guarantees asymptotic stability. By tuning the parameters of SMC, fast convergence of the error may be achieved, the control gain is increased which results severe chattering on the sliding surface These problems motivate the current research to improve the existing results.
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