Distributed Nonlinear Model Predictive Control by Sequential Linearization and Accelerated Gradient Method
Journal article, Peer reviewed
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OriginalversjonIFAC-PapersOnLine. 2016, 49 (7), 597-602. 10.1016/j.ifacol.2016.07.408
A suboptimal approach to distributed NMPC for nonlinear interconnected systems subject to constraints is proposed. The objective is to develop a computationally efficient approach. The suggested method is based on a sequential linearization of the nonlinear system dynamics and finding a suboptimal solution of the resulting Quadratic Programming problem by using distributed iterations of the dual accelerated gradient method. The benefits of the approach are reduced complexity of the on-line computations, and simple software implementation, which makes it appropriate for embedded distributed convex NMPC. The proposed method is illustrated with simulations on the model of a quadruple-tank system.