Abstract
This paper proposes a robust control scheme based on the sequential convex program-ming and learning-based model for nonlinear system subjected to additive uncertainties.For the problem of system nonlinearty and unknown uncertainties,we study the tube-based model predic-tive control scheme that makes use of feedforward neural network.Based on the characteristics of the bounded limit of the average cost function while time approaching infinity,a min-max opti-mization problem(referred to as min-max OP)is formulated to design the controller.The feasibil-ity of this optimization problem and the practical stability of the controlled system are ensured.To demonstrate the efficacy of the proposed approach,a numerical simulation on a double-tank sys-tem is conducted.The results of the simulation serve as verification of the effectualness of the pro-posed scheme.
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