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Title:Explicit use of probabilistic distributions in robust predictive control of waterborne AGVs - a cost-effective approach
Authors:H. Zheng, R.R. Negenborn, G. Lodewijks

Conference:15th European Control Conference (ECC16)
Address:Aalborg, Denmark
Date:June/July 2016

Abstract:This paper proposes a novel cost-effective robust Model Predictive Control (RMPC) approach that can handle stochastic uncertainties with infinite support. The proposed controller is applied to waterborne AGVs with uncertain predicted environmental influences due to wind, waves and currents. The approach is cost-effective in the sense that a trade-off is made among safety level, system performance/conservativeness, and problem solvability, achieved by explicitly considering system and uncertainty properties. Particularly, probabilistic distributions are modeled and integrated in a tube-based RMPC framework. The uncertainty bounds tightening system constraints and the corresponding probability being penalized for deviating from a desirable probability in the cost function are decision variables in online optimizations. Furthermore, successive linearizations of nonlinear system dynamics and nonconvex system constraints are implemented for ease of computational complexity and controller design. Simulation results are presented to demonstrate the effectiveness of the proposed robust control design and its application to waterborne AGVs.

Reference:H. Zheng, R.R. Negenborn, G. Lodewijks. Explicit use of probabilistic distributions in robust predictive control of waterborne AGVs - a cost-effective approach. In Proceedings of the 15th European Control Conference (ECC16), Aalborg, Denmark, pp. 1278-1283, June/July 2016.
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