System identification and control of the horizontal motion of a twin rotor multi-input multi-output system (TRMS)

Abstract

Rescue helicopters are often required to hover in certain motion, and most likely to maintain in still-air position for lifting purposes. the vibration produced by a helicopter during still-air hovering creates complexity in the physical control by the pilot, especially in the horizontal motion. to develop an optimum control system for the horizontal motion of such condition, the operating system must first be identified. a system model of an experimental test rig representing the twin rotor multi-input- multi-output system (trms), similar to a helicopter system needs to be developed before designing a controller to control this vibration. the objectives of this project are to identify the model and develop the controller for the horizontal motion of a trms. previous studies has shown that parametric modelling involving auto regressive with exogenous input model using recursive least squares algorithm, and non-parametric modelling involving nonlinear autoregressive with exogenous input model using multilayer perceptron neural network modelling are suitable to model the trms system, with acceptably low mean square error. the project is done by reviewing the trms dynamic modelling and control methodology. the collection of data from the trms system will be simulated and identified as the dynamic trms. a proportional-integral-derivative controller is developed based on the system identification model, using heuristic and automatic tuning techniques within matlab environment. the performance of the controllers thus developed is verified and validated by simulation on matlab simulink. the objectives are achieved when the controller is proven to be stable with significant reduction of vibration in the horizontal motion.