Search results

The purpose of this paper is to present the importance of model accuracy in closed loop control by the help of parallel finite element model of a voltage-fed solenoid with iron core.

The axisymmetric formulation of the domain decomposition-based circuit-coupled finite element method (FEM) is embedded in a closed loop control system. The control parameters for the proportional-integral (PI) controller were estimated using the step response of the analytical, static and dynamic model of the solenoid. The controller measures the error of the output of the model after each time step and controls the applied voltage to reach the steady state as fast as possible.

The results of the closed loop system simulation show why the model accuracy is important in the stage of the controller design. The FEM offers higher accuracy that the analytic model attained with magnetic circuit theory, because the inductance and resistance variation already take into account in the numerical calculation. Furthermore, parallel FEM incorporating domain decomposition to reduce the increased computation time.

A closed loop control with PI controllers is applied for a voltage driven finite element model. The high computation time of the numerical model in the control loop is decreased by the finite element tearing and interconnecting method with direct and iterative solver.

Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process.

To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process.

The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine.

The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design.