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Implementation of model predictive control on the pitch motion of train simulator platform with load torque uncertain
Ramelan A.a, Syaichu-Rohman A.a, Kelana A.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.This paper presents an analysis of the non-linearity of the torque load on the pitch platform movement of train simulator. Angle modelling of pitch available in many researches. However, for the changes of torque loads in the train simulator there has been no research that examines it. Then, this is one of the novelty we provided in this research. Beside that, we simulate Model Predictive Control (MPC) with a plant that contains non-linearity using simulation tool. In order to show the performance, we analyze its data and make a conclusion. As a Linear Quadratic Regulator (LQR), MPC produces an optimal control signal that can overcome constraints such as saturation. In MPC implementation, we determine the number of horizons (N), weighting Q and R based on the desired specifications.. The simulation results showed that the MPC design can handle non-linearity well. However, it is merely a simulation. We have not applied it to a actual plant yet.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Linear quadratic regulator,Load torques,Non linear,Optimal controls,pitch,Pitch motion,Torque loads,Train simulators[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]mpc,non-linear,pitch,torque,train simulator[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]ACKNOWLEDGMENT This research was supported by the LPDP Scholarship from Indonesian Ministry of Finance, and also full supported by School of Electrical Engineering and Informatics, Institut Teknologi Bandung, especially Control and Intelligence System Research Group.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICSEngT.2018.8606362[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]