Specification of an intelligent simulation-based real time control architecture: Application to truck control system

The paper presents an implemented architecture of an intelligent simulation-based real-time control (SRTC) system for industrial applications. The proposed SRTC uses a trajectory tracking strategy inspired from the model-based predictive control approach. Dynamic control law based on the closed-loop feedback correction is embedded. A computer implementation of this control scheme and experiments are conducted for real-time truck dispatching on a surface mine transportation system. Results showed the capability of the SRTC to generate efficient real-time truck dispatching orders at each 120 s. Simulation results demonstrate that managing trucks with such dynamic control law improves productivity. This improvement is reached when the transportation system is under steady as well as transient states conditions. The proposed SRTC makes use of the intelligent metaheuristic optimization search even under tight timeliness constraints.

► A simulation-based real-time control system for industrial applications is proposed. ► The predictive module is based on discrete event simulation rather than the classical analytical modeling approach. ► The system makes use of the intelligent metaheuristic optimization search even under tight timeliness constraints. ► Experiments demonstrated performance improvement when this system is used for management under stochastic environments.