A new hybrid intelligent control algorithm for a seven-link biped walking robot

Abstract

In recent years, many studies on bipedal walking robots and control algorithms have been conducted. However, different conditions and circumstances that have to be taken into account make the control of biped walking robots a big challenge. This paper proposes the implementation of a new hybrid intelligent control approach for a seven-link biped walking robot to track the specified trajectory based on a compensatory neurofuzzy network and fuzzy controller. This algorithm consists of two main parts: the feedforward compensator includes an integrated compensatory neurofuzzy network for identification of the inverse dynamics model which attempts to cancel the dynamics of the robot, and the feedback controller which includes a Mamdani-type fuzzy controller to compensate the modeling error and the effect of noise on the system. Moreover, a new style of membership functions distribution for fuzzy controller with noise reduction capability is proposed and its influence on the performance of the robot under noise-free and noisy conditions is investigated. Simulations performed on a biped robot illustrate the methods and their performance. The results confirm the high tracking capability and effectiveness of the proposed control approach.