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Implementation of sliding mode control using modification of two-steps LMI approach for speed control of electric vehicle simulator
Santabudi M.R.A.R.a, Rohman A.S.a, Hindersah H.a, Prasetyo H.F.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]© 2017 IEEE.Along with the advanced development of electric vehicles today, the control process for electric vehicles is also increasingly needed, one of which is the speed control of electric vehicles. This paper describes the speed control of electric vehicles simulator consisting of two BLDC motors that acting as a motor simulator and as a load simulator. This research use Arduino Mega microcontroller as the controller and MATLAB for the simulation purpose. In this study, the method of Sliding Mode Control (SMC) with a modification of two-steps Linear Matrix Inequality (LMI) approach will be implemented to control the speed of electric vehicle simulator. The modification here is adding an integrator in the SMC two-steps LMI approach system. This method is applied with the assumption that the system used is Linear Time-Invariant (LTI) and continuous. This method ensures that the closed loop system with the controller is stable in the sense of Lyapunov. The results of this research show that the design result of SMC controller with a modification of two-steps LMI approach is as expected. The simulations performed with MATLAB have resulted in a stable system response and can track the input given. Even with the load that simulating the frictional, drag, and gravitational forces both in downhill and uphill condition, the system is still meet the stable and tracking condition. Likewise, the results of the implementation of BLDC motor have shown a same result as the simulation, but with some errors that can be produced from sensor error, filter error, and the system model error.[/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]Adding an integrators,BLDC motors,Gravitational forces,Linear matrix inequality approach,Linear time invariant,Sliding mode control(SMC),System modeling,Vehicle 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]BLDC Motor,EV Simulator,LMI,SMC,Speed Control[/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/ICEVT.2017.8323531[/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]