Zhou Zu-de

Fuzzy-immune PID control for AMB systems

In order to improve the dynamic performance of active magnetic bearing systems with highly nonlinear and naturally unstable dynamics, a new nonlinear fuzzy-immune proportional-integral-derivative (PID) controller is proposed by combining the immune feedback law with linear PID control. This controller consists of a PID controller and a basic immune proportional controller in cascaded connection, the nonlinear function of the immune proportional controller is realized by using fuzzy reasoning. Simulation results demonstrate that the active magnetic bearing system with the proposed controller has better dynamic performance and disturbance rejection ability than using the linear PID controller.

Robust Optimization and Simulation of Production/inventory System with Stochastic Demand

In this paper a multi-stage multi-item production/inventory system with limited production capacity in stochastic demand environment is considered. We proposed a robust optimization model to deal with the uncertain market demands that are denoted as a number of discrete scenarios with known probabilities. An effective genetic algorithm is designed. The result of a simulation example shows that robust optimization is possible. By choice of proper programming weight omega, we can meet the stochastic demand with little error and very little cost.