2020/01/01 by Xuehui Gao, Xinyan Hu · 1 citation
Engineering · #Tailings Management and Properties #Mineral Processing and Grinding #Geoscience and Mining Technology #Petri net #Nonlinear system #Artificial neural network #Process (computing) #Computer science #Control theory (sociology) #Bernoulli's principle #Function (biology) #Lyapunov function #Controller (irrigation) #Engineering #Control (management) #Algorithm #Artificial intelligence
paper · pdf · doi:10.1109/access.2020.2968510
openalex publication_date 2020/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/26
In mining industries, the backfill becomes more and more important due to the environment protection concern. But most backfill investigations focus on the underground model and backfill materials. In this research, the paste backfill process based on the process control is investigated and a new paste backfill process model is proposed according to the Torricelli's law and Bernoulli principle. In order to deal with the unknown nonlinear function of the proposed backfill model, a Petri net(PN) structure is presented and a new Petri net neural network(PNNN) is introduced to approximate the unknown nonlinear function. Then, a robust controller is designed for the backfill process with PNNN and the closed loop stability is guaranteed by Lyapunov function candidate. The effectiveness of the proposed model with new PNNN and the robust controller are verified by simulation results.