<p style='text-indent:20px;'>Injection speed control is one of the most essential components in the injection molding process. It is critical to implement fast and reliable injection speed optimization control for the effective manufacturing of injection molding products. In this paper, the speed tracking control problem of the hydraulic cylinder of an injection molding machine driven by a typical servo motor is studied. An efficient two-stage optimization framework that leverages the ideas of both control parameterization (CP) and particle swarm optimization (PSO) is proposed for generating the optimal signal input to achieve the required injection speed tracking over a certain time. To this end, the dynamic model of the hydraulic system in the injection molding equipment is firstly established and the optimal controller design problem is transformed into sequential optimal parameter decision problems, and the explicit expressions of the gradient information of the objective function as well as the constraint on the parameters of the decision variables are derived. Then, the PSO combined with the CP and gradient-based algorithm is utilized to to solve the parameters of the controller efficiently. The two-stage optimization framework proposed in this paper can improve the convergence speed of the CP method and the precision of the PSO and easy-to-implement in engineering and industrial deployment. Finally, the feasibility and effectiveness of the proposed design method are verified by experimental simulations.</p>
Injection molding is a critical component of modern industrial operations, and achieving fast and stable control of injection molding machines (IMMs) is essential for producing high-quality plastic products. This paper focuses on solving an optimal tracking control problem of the injection velocity that arises in a typical nonlinear IMM. To this end, an efficient optimal robust controller is proposed and designed. The nonlinear injection velocity servo system is first approximately linearized at iteration points using the first-order Taylor expansion approach. Then, at each time node in the optimization process, the relevant algebraic Riccati equation is introduced, and the solution is used to construct an optimal robust feedback controller. Furthermore, a rigorous Lyapunov theorem analysis is employed to demonstrate the global stability properties of the proposed feedback controller. The results from numerical simulations show that the proposed optimal robust control strategy can successfully and rapidly achieve the best tracking of the intended injection velocity trajectory within a given time.
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