MPC-based setpoint compensation with unreliable wireless communications and constrained operational conditions

This paper studies operational optimization design in industrial processes with constrained operational conditions when the operational state is transmitted via wireless networks, inducing noise and packet dropout which negatively affect operational optimization performance. Firstly, given a constrained-input process, a PI controller is designed to stabilize the plant without any steady-state error for setpoint tracking. Secondly, a stochastic noise and packet dropout model is established by analyzing the characteristics of data transmission in wireless networks, and is used in designing an setpoint optimization controller based on state feedback. Specifically, a condition to guarantee asymptotic stability and optimal operational index tracking of the dual-layer closed-loop system is given. Finally, a semi-physical simulation experiment in a flotation process is employed to demonstrate the effectiveness of the proposed method.