Model-free Adaptive Control Strategies Based Approaches To Multilayer Process Goose Queue(Pgq)Formation Adjustments

The Process Goose Queue(PGQ)is a new approach to solve the decomposition-coordination-optimization problems of process production systems.At present,the existing multilayer PGQ formation adjustment is generally carried out with model-based optimization approaches,which still suffer some shortcomings,such as:1)Unmodeled dynamics and other uncertainties are always unavoidable in the modeling process,which may lead to poor robustness of the closed-loop control system.2)In actual industrial processes,considering each PGQ is generally a multi-input multi-output element,it is hard to obtain coupling relationship between inner variables of PGQ as well as the decoupling state space model.In response these limitations,this paper presents a:model-free adaptive control strategies based approaches to multilayer Process Goose Queue(PGQ)formation adjustments.The main research contents are presented as follows.Firstly,a dynamic linearization method for discrete-time nonlinear systems is introduced in detail,and the CFDL(compact form dynamic linearization)data model of discrete-time nonlinear system is given.On this basis,the derivation process of CFDL-MFAC control scheme for nonlinear systems is completed,and the proof of relevant definition has been given.In addition,for current MFAC control program,we analyzed its defects in process industry applications;the aim is for further improvement.Secondly,aiming at the existing problems in multilayer PGQ formation adjustment,we use CFDL data model to replace the identification and modeling process at all levels.And through the introduction of inter-stage coordination matrix and inter-stage feed-forward,we propose a multilayer PGQ formation adjustments algorithm based on MFAC strategy.Finally,the TE process is used to verify this method.The experimental results show that this method has good dynamic characteristics,could effectively deal with the coupling relationship between internal variables of each subsystem and the coupling relationship between subsystems,suppressed the spread of interference at all levels,achieved real-time online adjustment of multilayer PGQ formation.