Research Of Multi-variable Adaptive Control System And Application In Gas Treatment Process

The majority of industrial control systems in modern times can be abstracted mathematically as discrete multivariable nonlinear systems.However,traditional control methods and systems face limitations when dealing with the adaptive control problems presented by such systems.Therefore,this study focuses on the research and improvement of multivariable adaptive control for these types of systems,particularly in the context of controlling exhaust gas treatment processes.(1)A modified model-free multivariable adaptive control method based on tight format dynamic linearization(IMMFAC)is proposed to address the adaptive control problem of a class of discrete multivariable nonlinear systems.Digital simulations demonstrate that adding proportional-integral terms not only reduces the initial oscillation of the MFAC method but also improves its tracking performance,real-time capability,and generalization.(2)To address the issue of multiple tunable parameters in the IMMFAC method,a novel parameter tuning framework called MPSA-WOA is proposed.Digital simulation experiments show that applying parameter tuning to the IMMFAC method further enhances convergence speed and tracking performance.(3)For exhaust gas treatment processes with multiple intercoupled control variables,a control strategy combining a key variable identification model and the IMMFAC method is proposed.Simulation results demonstrate that this controller effectively reduces the emission concentration of various pollutants in exhaust gas.(4)By comparing the performance of terminals,microservers,and microcontrollers from different perspectives,an architecture for an exhaust gas treatment process control system based on edge computing is proposed.Detailed analysis and implementation of some functional modules of the control system are conducted.Compared with the lumped control system based on the PID control method,the IMMFAC method and the edge-type tail gas treatment process control system that implements the WPSA-WOA parameter tuning algorithm offer several advantages.1)The data-driven IMMFAC method could more effectively deal with strongly nonlinear and strongly coupled systems and improve the control quality.2)It enhances the computing power and interaction ability of the edge side,solves the problem of multicontroller communication and cooperation,and provides a basis for running modern intelligent control algorithms.3)It leverages the tail gas treatment process data to improve the efficiency of the tail gas treatment process and further reduce the environmental protection cost of the enterprise.