Supervisory Adaptive Network-Based Fuzzy Inference System (SANFIS) Design for Empirical Test of Mobile Robot

Abstract

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.

Image processing based obstacle avoidance control for mobile robot by recurrent fuzzy neural network

“…There are two RFNNs controllers should be designed. the following relation equations are considered [5]: …”

“…These active sensors just can give one-dimensional information such as distance or range but they are difficult to give the angle or vertical variation information. In my previous work [5], a good tracking control performance of mobile robot has been presented as it just can do path control but can not do obstacle avoidance control, meanwhile, it uses infrared sensor instead of camera sensor.…”

Machine vision based sliding fuzzy-PDC control for obstacle avoidance and object recognition of service robot platform

“…Fuzzy logic control has been developed for a long time and it has become a powerful methodology to deal with many control problems especially for the robot control [7,8]. Among the many fuzzy methodologies, the fuzzy-PDC design approach was proposed and be attractive since it is simple and natural.…”

Sliding mode multi-ANFIS (SMANFIS) control for vision robot

“…[t has been used in every area of reasearches widely and successfully for the reason of it possesses efficient learning ability and easy implementations. Its related applications can be found in [2][3][4]. However, by using the ANF[S controller alone, better performences cannot be easy achieved, so in this paper, another combination of multi-ANF[S (MANF[S) approach is proposed to deal with a control prolem of vision robot.…”