改进无模型自适应控制方法研究-检测技术与自动化装置专业论文.docxVIP

Abstract Abstract 万方 万方数据 Title: THE IMPROVEMENT OF MODEL-FREE ADAPTIVE CONTROL Major: Detection Technology and Automatic Equipment Name: Juan Jiang Signature: Supervisor: Prof. YanXi Yang YiDeng  Abstract Signature: Signature: Model-仕ee adaptive control(MFAC) is a typical method of Data-driven control，its controller design can be achieved just by using only the off1ine and online I10 data of the system，without needing to know the mathematical model of the controlled system，and when the system parameter or structure changes，it also can achieve good adaptive control. This control method has made many achievements in practical application. This paper firstly introduces the basic theory of the model-free adaptive control and basic conception of universal model ，then analyzes its stability and convergence. Model-free adaptive control based on compact form dynamic linearization and model-free adaptive control based on partial form dynamic linearization algorithm are realized in Matlab，and a series of simulation experiments for some typical nonlinear system are carried out. This chapter studies the effect of control par缸丑eters λ 、ρ 、η 、μ on the system dynamic performance ，especially for the circulating fluidized bed boiler bed temperature control under different loads，the simulation experiment results show that MFAC method can adapt to changeable models during boiler combustion process ，and obtain good control performance. Secondly，in view of the measurement disturbance problem of model-企ee adaptive control， the influence of the measurement disturbance is analyzed，and proposes a improved algorithm-model free adaptive control method with tracking differentiator. Tracking differentiator(TD) ，part of active disturbance rejection control (ADRC) ，is added to the model-free adaptive control as a feedback filter ，uses its filter characteristics to separate output signal 丘om the noise signals，thus effectively suppressing measurement interference and enha