Simulated annealing procedure for on-line control with process dynamics

We study the problem of economic design for a control policy where the sampling interval (m) and control limit (d) are determined by minimizing the expected total quality costs. In this article, we propose a simulated annealing scheme applicable to an economic design for a control policy where the disturbances can follow the autoregressive integrated moving average (ARIMA) processes and obtain the optimum d and m. Numerical investigations are conducted for a system with a first-order dynamics subjected to an IMA (1,1), and an ARI (1,1) random disturbance. The performance of the proposed simulated annealing scheme is very promising and compares favorably to other methods.