Augmented state estimation and LQR control for a ball and beam system

Based on the strong tracking filter (STF), a STF-LQR control approach is presented for the control of a ball and beam system (BBS). The simple linearized mathematical model of the BBS is first obtained according to physics laws. In order to model the BBS accurately, an additional control action is introduced as an augmented state variable to compensate for the unmodeled dynamics, such as friction, nonlinearity, disturbance and time-varying characteristics. All the states are adaptively estimated by using the STF, and the controller is designed by employing the discrete-time LQR technique. A BBS control test rig is built based on the NetCon system. Practical experiments have been carried out to demonstrate the feasibility and effectiveness of the proposed approach.