Moving path following control of constrained underactuated vehicles: A nonlinear Model Predictive Control Approach

R. Praveen Jain; Andrea Alessandretti ; António Pedro Aguiar; João Borges de Sousa.

 AIAA Information Systems-AIAA Infotech at Aerospace, 2018 

ID Authenticus: P-00N-T0N

DOI: 10.2514/6.2018-0509

Abstract: This paper addresses the design of a stabilizing continuous time sampled-data Nonlinear Model Predictive Control (NMPC) law to solve the Moving Path Following (MPF) motion control problem for constrained under-actuated robotic vehicles. In this scenario, the robotic vehicle is tasked to converge to a desired geometric path, expressed with respect to a moving frame of reference, while satisfying the actuation constraints. This control problem is addressed in the NMPC framework. Specifically, first a suboptimal Lyapunov-based nonlinear auxiliary control law is designed to solve the MPF problem. Then, the latter is used for the design of a suitable terminal set and terminal cost of the MPC controller to enforce closed-loop guarantees. Exploiting the properties of the auxiliary control law, we show that for a suitable selection of the input constraints, the terminal set can be removed, resulting in a global region of attraction of the proposed controller. Simulation results are provided to illustrate the proposed control strategy.

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