Adaptive Control For Dual-Rate Sampled-Data Systems

The conventional sampled-data systems,whose outputs are sampled at the same rates as the control updating rates,are called single-rate systems.In many industry applications (especially in the chemical industry processes),the outputs are sampled at slower rates than the control updating rates,mostly due to hardware limitation.In this case,there will be two or even more different operation rates in a system.Such systems are named as dual-rate (multirate) systems.Therefore,how to control dual-rate(multirate) systems effectively is not only significant in theory,but also potentially values in applications.This thesis is based on the Project "Study of Modelling and Identification of a Class of Nonlinear Systems(The National Nature Science Foundation of China)",and researches adaptive control of dual-rate systems.Based on some existing identification and control methods of dual-rate(multirate) systems,the thesis mainly focuses on the adaptive control of controlled auto-regressive dual-rate systems.By combing different identification methods with different control schemes,new algorithms of adaptive control are obtained,and results are presented as follows.1.By directly using dual-rate data or polynomial transformation technique and least square or stochastic gradient identification methods,four dual-rate adaptive control algorithms are proposed based on the minimum variance control strategy.Simulation examples are also given to demonstrate the control performance.2.Because of the fact that the minimum variance control strategy cannot satisfy the stability of non-minimum phase systems,the traditional control strategy is adopting pole-placement control methods.The idea of dual-rate is extended to the pole-placement adaptive control in this thesis,and the dual-rate methods based direct ly on dual-rate data and the polynomial transformation technique are also analyzed.A simulation example is given to demonstrate the dynamic response and stability of dual-rate pole-placement control method.3.Because systems in process industry are almost nonlinear systems,this thesis also discusses the adaptive control of dual-rate nonlinear systems.Under the condition of knowing or unknowing input nonlinearities of Hammerstein systems,the adaptive control algorithms, based on least square and stochastic gradient,are proposed respectively.The performance of those algorithms are also discussed in detail.Finally,a simple conclusion of this thesis is given.The difficulties and further objectives of dual-rate problems are also simply outlined in the end.