Hierarchical adaptive network based fuzzy logic controller design for a single flexible link robot manipulator
In this study, hierarchical adaptive network based fuzzy logic controller for a single flexible link robot manipulator is designed. This study is aimed to get the end of the flexible robot manipulator to desired position and terminate vibrations on arm while it moves under the action of an external driving torque. The proposed controller has two subsystems. The fast-subsystem reduces the vibration of the flexible robot manipulator end point, and the other slow-subsystem controller controls the desired position. The performance of the proposed control system is evaluated on the basis of the experimental results.
Summary form only given, as follows. A study is presented of precision constraints imposed by a hybrid chip architecture with analog neurons and digital backpropagation calculations. Conversions between the analog and digital domains and weight storage restrictions impose precision limits on both analog and digital calculations. It is shown through simulations that a learning system of this nature can be implemented in spite of limited resolution in the analog circuits and using fixed-point arithmetic to implement the backpropagation algorithm. >