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This paper presents a new nonlinear model predictive control (NMPC) strategy based on the Gaussian particle swarm optimization (GPSO). Through the Taylor expansion, NMPC transform to a quadratic programming problem with unknown parameters. Hence, for the global convergence character and higher optimization accuracy, GPSO is employed to dynamically perform nonlinear constraint optimization. Finally, the proposed control strategy is applied to Ball-Plate system to verify the effectiveness.