Research On Disturbance Suppression Method Of Nonlinear System Based On U-model

Nonlinear systems are the most common control problems in control system design,and their controller design often leads to solving higher-order differential equations,which is difficult to obtain accurate analytical solutions.In addition,nonlinear systems often have immeasurable perturbations and noise,making controller design and solution more difficult.Different from the traditional physics-based model or data-driven model,U-model technology can describe the nonlinear controlled object as a polynomial form composed of different orders of system inputs and time-varying parameters,and use the linear controller design method to design the nonlinear control system without losing the nonlinear characteristics,which can simplify the controller design process.The research on disturbance suppression of nonlinear system based on U model is mainly based on disturbance observation and compensation methods.In the existing research,the control law disturbance compensation form of this method is rarely studied,and the design method of disturbance observation link needs to be supplemented.In conclusion,for the general nonlinear system under bounded disturbance,in order to achieve accurate control,this paper uses the disturbance observation and compensation method to study the disturbance suppression problem based on the U model.An intelligent control method is introduced to optimize the controller and disturbance observer to achieve better disturbance suppression effect.The main work of this article is as follows:(1)Aiming at the tracking control problem of a class of nonlinear systems under bounded disturbances,a fuzzy immune automatic disturbance rejection control(FIUADRC)method based on U model is designed.Firstly,the U-model is used to simplify the original nonlinear system.Fuzzy immunoassay(FI)technology is used to optimize the control law coefficient,output the pseudo-control quantity of the system,equivalentize the observation state error to the number of antigens,and suppress the perturbation that is not accurately estimated and compensated.The pseudo-control quantity and its variation amount are used as fuzzy input,and the fuzzy output is updated according to the immune principle,and the inhibitor is adjusted to eliminate the approximate error of the inversion process of the U model.Secondly,the Lyapunov method is used to prove the stability of the system.Finally,taking the Hammerstein model and the continuous stirred kettle reactor(CSTR)system as an example,and comparing it with the UADRC algorithm,the results show that the proposed method is superior to the UADRC algorithm in terms of immunity adjustment speed and tracking accuracy.(2)Aiming at a class of nonlinear systems with unknown interference,a disturbance observer based on fuzzy cerebellar model control(FCMAC)technology is proposed,and a U-model fuzzy cerebellar interference observer control(UFCMAC)algorithm is designed.Firstly,the controller design is carried out based on the U-model transformation,the interference observer is designed by the FCMAC method,the disturbance information is observed online,and the disturbance compensation control quantity is output according to the disturbance observation measurement,observation error and systematic error.In order to quickly approach the zero system error,proportional-derivative(PD)control is adopted,and the PD and disturbance compensation control quantities are composed of U model pseudo control quantities.Finally,taking the aircraft model as the controlled object,the tracking control system of drag acceleration-energy standard trajectory is designed and simulated,and the simulation results show that the proposed algorithm can effectively realize input tracking and disturbance control through online reconstruction and disturbance compensation.(3)The comparative simulation of the FI-UADRC and UFCMAC methods proposed in this paper shows that the UFCMAC method has a longer execution time but smaller tracking error.In short,the UFCMAC method and the FI-UADRC method each have different advantages and scope of application.This also shows that for different nonlinear control problems,different control methods need to be adopted to achieve more accurate and robust control effects.