Nonlinear Design of Model Predictive Control Adapted for Industrial Articulated Robots

This paper introduces a specific nonlinear design of the discrete model predictive control based on the features of linear methods used for the numerical solution of ordinary differential equations. The design is intended for motion control of robotic or mechatronic systems that are usually described by nonlinear differential equations up to the second order. For the control design, the explicit linear multi-step methods are considered. The proposed way enables the design to apply nonlinear model to the construction of equations of predictions used in predictive control. An example of behavior of proposed versus linear predictive control is demonstrated by a comparative simulation with nonlinear mathematical model of six-axis articulated robot.

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