Simulation-Based Optimization for the Fast Fashion Replenishment

Fast fashion is a commercial pattern which provides fashionable clothes at affordable price.This mode needs rapid response supply chain to respond to varying fashion trends.New styles are introduced in every sale period to cover fashion trends.In order to maximize profits,replenishment quantity of each style should be decided in every period.The purchasing and replenishing process over multiple periods based on uncertainty customer demand is modeled,which is formulated by a stochastic choice process.Heterogeneous consumers visit a store in a stochastic sequence and choosing dynamically from the available fashion styles(buy or not buy) according to a utility maximization criterion.The purchase process in a retail shop for multi-period is simulated.An algorithm which combines simulated anneal(SA) with gradient estimation is proposed to find the optimal replenishing strategy from the simulation program.

Feed-Forward-Like Decoupling Control in Coagulation Bath of Carbon Fiber Precursor

The coagulation bath system of carbon fiber precursor is a complicated and multivariable coupling system. Based on the model of industrial production,the full dynamic decoupling control of the coagulation bath system of carbon fiber precursor is achieved in combination with multivariable feed-forward-like decoupling and proportional-integral-differential( PID) control. Compared with the conventional PID decoupling control,the experiment results show that the proposed method has a better control effect. The use of the controller can achieve complete decoupling of three parameters from coagulation bath system. The method should have great applications.

Boundary Control for an Unstable Wave Equation in Annular with Symmetrical Initial Data

A problem of boundary stabilization of a wave equation with anti-damping term in annular is considered.This term puts some eigenvalues of the open-loop system in the right half of the complex plane.Suppose the initial and boundary conditions are rotationally symmetric,the equation in two-dimensional(2-D)annular is transformed to an equivalent one-dimensional(1-D)equation in polar coordinates.A feedback law based on the backstepping method is designed.By a successive approximation,it's proved that there exists a unique solution of the integral kernel which weights the state feedback on boundary.It's also proved that the energy function of the closed-loop system decays exponentially,implying the exponential stability of the closed-loop system.The effectiveness of the control is illustrated with numerical simulations.

Adaptive Neural Network Control for Euler-Lagrangian Systems with Uncertainties

An adaptive controller involving a neural network(NN)compensator is proposed to resist the uncertainties in the Euler-Lagrangian system(ELS).Firstly,a proportional-differential(PD)control law is designed for the nominal model.Meanwhile,the uncertainties including model error and external disturbance are separated from the closed-loop system.Then,an adaptive NN compensator based on the online training mode is proposed to eliminate the adverse effect of the uncertainties.In addition,the stability of the closed-loop system is proved by Lyapunov theory.Finally,the effectiveness of the proposed approach is verified on a two-degree-of-freedom robot manipulator.