MODEL PREDICTIVE CONTROL OF CONE CRUSHER BASED ON ORTHONORMAL BASIS LAGUERRE FUNCTIONS

In this paper, model predictive control of cone crusher using orthonormal basis functions for control vector parameterization is showed. This approach has reduced the computational complexity and increase the controller speed. A comparative analysis of the parameters influence on the closed-loop system response quality is implemented. Settling time depends on the Laguerre model order and scaling factor as well as the prediction horizon. Overshoot occurs at short prediction horizon (1 3 samples) or scaling factor values less than 0.5. Overshoot can be reduced by changing constraints on the amplitudes of control. A number of limits on the control does not affect closed-loop response through receding horizon control principle. All model predictive control schemes are provided zero steady-state error. The control vector parameterization based on orthonormal basis functions will be used to the design nonlinear model predictive control application.