Abstract
The paper presents a software implementation of the nonlinear model predictive control (NMPC) algorithm of Wen and Jung (2002, 2003) to a 6-degree-of-freedom robot manipulator. The implemented algorithm attempts to reduce the error at the end of the prediction horizon rather than to find the optimal solution. This leads to reduction of computational burden. Simulations have been carried out for the mathematical model of the 6DOF robot manipulator (Puma 560) and some exemplifying results are presented.
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