Publications

Thesis

Investigations into new tunable fuzzy and modular neuro-fuzzy controllers

Resume

The chief aim of the work was to bring into sharp focus the utility of fuzzy logic controllers (FLC) and modular neuro-fuzzy logic controllers in a wide variety of situations.

A fuzzy logic controller was designed to control a process plant with widely varying conditions in its operations. The varying conditions considered were the order, type, time-delay and associated parameters. Disturbances at the input level and sudden set point variations were also considered to bring out the features of the FLC to the fore.

A neuro-fuzzy/fuzzy adaptive controller with four self-learned fuzzy control rules was also arrived at, to effectively control the above process plant.

Modern automobile industries are focusing a lot of attention on the (semi-) active suspension systems for good ride comfort, by bringing down the vertical acceleration and deflection as far as possible. A FLC designed for a quarter car system was found to exercise control in checking its vertical acceleration and deflection to a level, that of a hypothetical model. The same controller was found to contain a wide variations in the parameters of the suspension system without any modification whatsoever.

A modular neuro-fuzzy structure was proposed to position and to balance the cart-pole system. The two modules were made to learn the control strategies using temporal back propagation algorithm. The fuzzy de-compositional rule of inferencing has been used to arrive at the modular structure.

On a similar fashion a modular FLC was designed for the cart-pole system and its input-output mappings were captured with the help of a modular neuro controller. This will reduce the computational burden associated with the FLC, in its implementation stage.

These studies clearly demonstrated the utility, flexibility and robustness of fuzzy and/or neuro-fuzzy logic controllers in disparate applications.