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A supervisory Adaptive Network-based Fuzzy Inference System (SANFIS) is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off-line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error between the ANFIS controller and the ideal controller, and drive the trajectory of the system onto a specified surface (called the sliding surface or switching surface) while maintaining the trajectory onto this switching surface continuously to guarantee the system stability. This SANFIS controller can achieve favourable empirical control performance of the mobile robot in the empirical tests of driving the mobile robot with a square path. Practical experimental results demonstrate that the proposed SANFIS can achieve better control performance than that achieved using an ANFIS controller for empirical control of the mobile robot.

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An adaptive network based fuzzy inference system (ANFIS)-based integral terminal sliding (ITS) mode (ANFISITS) control is developed in this paper to deal with the disturbed chaotic systems. This ANFISITS control system is composed of an ANFIS controller and an ITS controller. The ANFIS controller is designed to approach an ideal controller and the ITS controller is designed to compensate for the approximation error between the ANFIS controller and the ideal controller; meanwhile, the ANFISITS control can cope with the disturbances. In simulations, the chaotic system control is illustrated to verify this proposed ANFISITS control system. The simulation results of the proposed control method possess better performance and robustness compared with that of fuzzy sliding parallel distributed compensation (FS-PDC) control.

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