Comparison of Kinematic and Dynamic Model Based Linear Model Predictive Control of Non-Holonomic Robot for Trajectory Tracking: Critical Trade-offs Addressed

Kaustav Mondal, Armando A. Rodriguez, Sai Sravan Manne, Nirangkush Das, and Brent Wallace


Nonholonomic System, Model Predictive Control, Convex Optimization, Trajectory Tracking Control, Quadratic Programming, Mobile Robot


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.

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