Observer based adaptive controller design of flexible manipulators using time-delay neuro-fuzzy networks

A dynamical time-delay neuro-fuzzy controller is proposed for the adaptive control of a flexible manipulator. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity. For perfect tracking control of the robot, an output redefinition approach is used in the adaptive controller design using time-delay neuro-fuzzy networks. The time-delay neuro-fuzzy networks with rule representation of a Takagi-Sugeno-Kang type fuzzy system have better learning ability for complex dynamics as compared with existing neural networks. The control structure and learning algorithm are given, and a simulation for the trajectory tracking of a flexible manipulator illustrates the control performance of the proposed control approach.