Modeling and Precision Stop Control of Metropolitan Train with Robust Output Feedback Model Predictive Control

Abstract

This thesis apply robust output feedback model predictive control (ROFMPC) for precision stop control of metropolitan train. For modeling the train, we consider actuation delay of train’s actuator, switching of actuators, nonlinearity of actuator’s saturation, so we consider a train as an nonlinear switching system. However, we consider a train as a uncertain linear system, because it is possible to obtain the exact train's acutator model. Therefore, ROFMPC is selected as controller for precision stop control of a train. We simulate precision stop control of a train with ROFMPC and evaluate the performance of ROFMPC. We compare ROFMPC and output feedback MPC (OFMPC) in performance of precision stop control of train. Also, we test for performance of ROFMPC under uncertain train’s mass and running resistance. Results show that ROFMPC is better than OFMPC and ROFMPC has robustness of uncertain train’s mass and running resistance. Because the state-feedback control's structure is included in robust MPC (RMPC)'s structure, we compare state-feedback control and RMPC in performance of simple model with disturbance. Also, we simulate the precision stop control of train using state-feedback control with state estimation because the result of simulation of comparison of RMPC and state-feedback control shows state-feedback control's step response is similar with RMPC's step response for the simple model with disturbance. As a result, state-feedback control with state estimation is appropriate for precision stop control of train and state-feedback control with state estimation is robust in performance of precision stop control of train under uncertain train's mass and running resistance. ⓒ 2017 DGIST