TY - GEN
T1 - Comparison of kinematic and dynamic model based linear model predictive control of non-holonomic robot for trajectory tracking
T2 - 2019 IASTED International Conference on Mechatronics and Control, MC 2019
AU - Mondal, Kaustav
AU - Rodriguez, Armando A.
AU - Manne, Sai Sravan
AU - Das, Nirangkush
AU - Wallace, Brent
N1 - Funding Information:
K.Mondal and N.Das are Ph.D. students in School of Elect., Computer & Energy Eng. (ECEE), Arizona State University (ASU), Tempe, AZ; S.Manne is a MS student in ECEE; Brent Wallace is a BS student in ECEE; Dr. A.A. Rodriguez aar@asu.edu is a Professor in ECEE, ASU. This work has been supported, in part, by National Science Foundation (NSF) Grant No. 1565177. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of NSF.
Publisher Copyright:
© 2019 Proceedings of the IASTED International Conference on Mechatronics and Control, MC 2019. All rights reserved.
PY - 2019
Y1 - 2019
N2 - This paper presents a hierarchical inner-outer control structure with model predictive controller (MPC) in the outer-loop and a PI controller in the inner loop, to perform trajectory tracking on non-holonomic robots. Two different MPC formulations are considered: (1) kinematic model based MPC which assumes that inner-loop has infinite bandwidth (2) dynamic model based MPC which takes into consideration the bandwidth limitations imposed by inner-loop. In order to emphasize the importance of dynamic model based MPC over kinematic model based MPC, critical tradeoffs involving tracking errors vs inner-loop bandwidth, for varying reference velocities, are studied. The novelty of this paper lies in the systematic approach taken to answer: (1) when is a kinematic model based MPC sufficient, (2) when is a dynamic model based MPC necessary, to obtain good trajectory tracking properties. Both, simulation and hardware results are taken into consideration.
AB - This paper presents a hierarchical inner-outer control structure with model predictive controller (MPC) in the outer-loop and a PI controller in the inner loop, to perform trajectory tracking on non-holonomic robots. Two different MPC formulations are considered: (1) kinematic model based MPC which assumes that inner-loop has infinite bandwidth (2) dynamic model based MPC which takes into consideration the bandwidth limitations imposed by inner-loop. In order to emphasize the importance of dynamic model based MPC over kinematic model based MPC, critical tradeoffs involving tracking errors vs inner-loop bandwidth, for varying reference velocities, are studied. The novelty of this paper lies in the systematic approach taken to answer: (1) when is a kinematic model based MPC sufficient, (2) when is a dynamic model based MPC necessary, to obtain good trajectory tracking properties. Both, simulation and hardware results are taken into consideration.
KW - Convex Optimization
KW - Linear Model Predictive Control
KW - Mobile Robot
KW - Non-holonomic system
KW - Quadratic Programming
KW - Trajectory Tracking Control
UR - http://www.scopus.com/inward/record.url?scp=85092017925&partnerID=8YFLogxK
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U2 - 10.2316/P.2019.860-017
DO - 10.2316/P.2019.860-017
M3 - Conference contribution
AN - SCOPUS:85092017925
T3 - Proceedings of the IASTED International Conference on Mechatronics and Control, MC 2019
SP - 9
EP - 17
BT - Proceedings of the IASTED International Conference on Mechatronics and Control, MC 2019
PB - ACTA Press
Y2 - 6 December 2019 through 7 December 2019
ER -