A neuro-fuzzy delay compensator for distributed control systems

This paper presents a neuro-fuzzy implementation of the delay compensator to reduce the variable sampling to actuation delay effects in distributed control systems. The delay compensator approach proposed the addition of a compensator to an existing distributed system in order to overcome the control performance degradation that results from the variable sampling to actuation delay that characterizes distributed implementations. The effectiveness of the neuro-fuzzy delay compensator is evaluated using a distributed control system with a pole-placement controller that does not take into account the delay introduced by the distribution of the controller and the results are compared with the ones obtained using neural networks in the implementation of the compensator.