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Design of MPC-based motion cueing for 4 DOF simulator platform
Aulia A.I.a, Hindersah H.a, Rohman A.S.a, Hidayat E.a
a Bandung Institute of Technology, School of Electrical Engineering and Informatics-STEI, Bandung, 40132, 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]© 2019 IEEE.Vehicle simulators are currently widely used for many reasons: user training, vehicle model testing, etc. Generally, vehicle simulator consists of visual simulation system and movement simulation system. Motion cueing is the part of movement simulation system which calculates the platform’s position to produce the feeling of real vehicle movement to the user while also considers the platform’s mechanical restrictions in its calculation and algorithm. This paper explains about the design of motion cueing system for Institut Teknologi Bandung’s simulator platform which has 4 degrees of freedom (DOF) for its movements. Currently, the implemented motion cueing system uses Classical Washout Filter (CWF) algorithm which suffers from the platform movement limitation that potentially causes false perceived sensation when the platform stops moving in its limits and unavoidable steady-state error which is caused by the algorithm itself. Thus, Model Predictive Control (MPC)-based motion cueing for 4 DOF simulator platform is developed to overcome this problem since MPC generally involves the plant’s model in its calculation. From the simulation, it can be inferred that MPC-based motion cueing has lower steady-state error compared to the CWF-based one. The performance can also be adjusted further by tweaking the weighting matrix that is used in the cost function. Lastly, the calculation of CWF-based motion cueing includes platform limits thus the platform operation is always within its limits.[/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]4 degrees of freedom,Motion Cueing Systems,Motion-cueing,Movement Simulation,Steady state errors,Vehicle simulators,Vestibular models,Visual simulation systems[/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]Human vestibular model,Model predictive control,Motion cueing,Vehicle 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][/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.2019.8906308[/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]