Distributed estimation based temperature control strategy focusing on the laminar cooling process

As a kind of typical cyber-physical systems(CPSs), industry cyber-physical systems(iCPSs) are becoming an emerging hot topic in resent years. As an important physical parameter during the hot rolling process, the performance of estimation and control of temperature has great impact on the quality of products. Therefore, this paper mainly focuses on the temperature control in the laminar cooling process via distributed estimation manners over wireless sensor networks. For the estimation process, a novel protocol of estimation: finite-time distributed average consensus Kalman filter is proposed. Compared to the conventional distributed estimation mechanism, this proposed approach uses the left eigenvector estimation and sliding mode techniques to meet the average consensus in finite time over directed sensor networks. For the control process, in order to improve control performance, we propose another joint control strategy which combines both sliding mode controller and H
₂
optimal robust controller together. The simulation results illustrate the effectiveness of proposed algorithms and highlight the improvements by the usage of these techniques.