System identification of a twin rotor multi-input multi-output system using adaptive filters with pseudo random binary input

This paper presents an investigation into the development of a parametric model of pitch movement of a twin rotor multi-input multi-output system (TRMS) using adaptive finite impulse response (FIR) models. The TRMS is a laboratory platform designed for control experiments. In certain aspects, its behaviour resembles that of a helicopter. It typifies a high-order nonlinear system with significant cross coupling between its two channels. The system is initially excited with PRBS signals of different bandwidths to ensure that all resonance modes are captured. The PRBS magnitude is selected so that it does not drive the system out of its linear operating range. Then, an adaptive FIR filter structure with LMS, NLMS, and genetic algorithm (GA) with LMS algorithms is investigated to identify the system and extract its parametric model. Effects of filter taps, step-size and system convergence are also studied. Performances of the employed techniques are assessed and presented in time and frequency domains.