Nonlinear Self-Tuning PID Controller for a Flexible Manipulator based on NARMAX Model

Abstract

This paper describes the design of a new self-tuning controller to control tip trajectory and tip deflection of a two-link flexible manipulator handling variable payloads based on nonlinear autoregressive with moving average and exogenous input (NARMAX) model. This proposed adaptive controller consists of a multivariate proportional integral and derivative (PID) feedback loop. The gains of the PID controllers are calculated in real-time based on the kinship between PID and generalized minimum variance control laws. Parameters of the NARMAX model are estimated in real-time using an adaptive filter based on the recursive least square (RLS) algorithms. Simulation results envisage that the NARMAX based selftuning controller tracks a desired tip trajectory while suppressing the tip deflection under load pick-up and release operation.