Approximate model predictive control of a 3-DOF helicopter

This paper presents the design and experimental validation of a nonlinear multivariable predictive controller for an educational 3-DOF helicopter system. The control strategy - Approximate Predictive Control (APC) - is based on a neural network model of the nonlinear plant and its linearization in each sampling instant. The control input is generated using the linearized model and a GPC control law. For this application, a previously published APC approach has been extended to MIMO systems, and was modified by introducing model parameter filtering to achieve the required control performance. Experimental results demonstrate good tracking and disturbance rejection performance of the proposed method.