Explicit use of probabilistic distributions in robust predictive control of waterborne AGVs-A cost-effective approach

Conference paper (2016)

Authors

H. Zheng Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
G. Lodewijks Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2016

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

This paper proposes a novel cost-effective robust Model Predictive Control (RMPC) approach that can handle stochastic uncertainties with infinite support. The robust controller is developed by explicitly considering system and uncertainty properties and is applied to waterborne AGVs against environmental disturbances due to wind, waves, and currents. Specifically, probabilistic distributions are modeled and integrated in tube-based RMPC with optimized uncertainty bounds. Furthermore, successive linearizations of nonlinear system dynamics and non-convex constraints are implemented for ease of computational complexity and the robust design. Simulation results are presented to demonstrate the effectiveness of the proposed approach.