Multi-Objective Optimal Control Method for the 6-DOF Robotic Crusher

Abstract

In order to achieve the best crushing effect of the 6-DOF robotic crusher, a multi-objective optimal control method for the 6-DOF robotic crusher has been proposed. Taking the mass fraction of crushed products below 12 mm, total energy consumption, effective energy consumption, output, and wear as the working indexes, and taking the suspension point, precession angle, and swing frequency of the mantle as the working conditions of the crusher, the working indexes under different working conditions are calculated. And, based on the above parameters, the optimization objective function of the 6-DOF robotic crusher is obtained. The weight determination method of fuzzy multiple attributes decision making (FMADM) is used to determine the equivalent wear and the optimization target weight. Compared with the original scheme, the output increases and the energy consumption decreases significantly. The results can be used as a reference for the control strategy of the 6-DOF robotic crusher. It can also be used as a reference for the design of a traditional cone crusher.

Keywords

• 6-DOF robotic crusher
• multi-objective optimization
• fuzzy multiple attributes decision making (FMADM)
• grey wolf optimization algorithm