Jun Wu

A state‐dependent autoregressive with exogenous variables (SD‐ARX) model whose functional coefficients are approximated by sets of radial basis function (RBF) networks is proposed to describe the dynamic behavior of a quad‐rotor in this paper. This model is identified offline and used as an internal predictor of a receding horizon predictive controller to address the quad‐rotor's attitude control issue. In addition, the physical constraints of the system have been also taken into account during the controller design process. The results of real‐time control on a quad‐rotor aircraft illustrate satisfactory modeling accuracy in a large operating range and good performance of control approach proposed in this paper.

Research and utilization of quadrotor helicopter in many areas is increasing because of its special flight performance. It is not easy to control a quadrotor whose dynamic characteristics are nonlinear, multivariable and stronglycoupled. A novel method is proposed to solve this problem, which adopts a MIMO RBF-ARX model to represent the nonlinear dynamics of quadrotor, and then based on a locally linearized ARX model that is obtained from the RBF-ARX model at a working-point, the state-feedback control law with LQR approach is proposed to control the quadrotor. The results of real-time control on a quadrotor helicopter illustrate the feasibility and efficient performance of the modeling and control approach presented in this paper. And this successful application to the quadrotor helicopter confirms the validity of the RBF-ARX model.