DESIGN OF INTELLIGENT CONTROL FOR A TWIN ROTOR MULTI-INPUT MULTI-OUTPUT SYSTEM (TRMS)

Abstract

Intelligent control is employed in situations where little a priori knowledge of the plant is known. Intelligent control has also been used to compensate for online system parameter variations, which may arise due to changes in operating points, component faults, plant deterioration, etc. Intelligent computational techniques have been utilized effectively to solve control problems for the past few years. Among them fuzzy systems, neural networks and genetic algorithms are the most used methods. This dissertation presents the designing of an intelligent control for a Twin Rotor Multi‐Input‐Multi‐ Output System (TRMS). The control objective is to make the beam of the TRMS move quickly and accurately to the desired positions, i.e., the pitch and the travel angles. Developing a controller for this type of system is challenging due to the coupling effects between two axes and also due to its highly nonlinear characteristics. In this dissertation accurate dynamic models of the system for both horizontal and vertical movements are developed so as to get very similar responses to that of the real plant. Also predictive control toolbox is used in an identification process to obtain neural network model for the horizontal part of Twin Rotor Multi Input Multi Output system (TRMS). The dynamic models are used as test‐beds to develop a set of intelligent controllers. The performances of fuzzy, neuro‐fuzzy controllers in tracking movements in both horizontal and vertical planes are found to be satisfactory. A comparative performance study of intelligent control approach with respect to a single PID approach is also presented in this study.