Application of Method of Adjustable Model for Identification of Linear Object with Uncertain Parameters and Disturbance

摘要

In a wide variety of parametric uncertainties and external disturbance estimation and attenuation methods uncertainties and disturbance are lumped together and an observation algorithm is employed to estimate the total disturbance. While in certain cases of application can be required the separate estimation or identification of uncertain parameters itself and a disturbance. In the paper the separate and simultaneous identification (estimation) of unknown and/or changing parameters and an external disturbance of a linear object is considered. For this porpose the known procedure of synthesis of adaptive observer for estimation of parameters and state coordinates of a n-th order linear object is used taking into account the influence of the scalar external disturbance operating on this object. Developed adaptive observer provides asymptotic stability of processes of separate and simultaneous identification of uncertain parameters and an external disturbance of a n-th order linear object. Asymptotic stability of proposed observer is proved by Lyapunov’s direct method. As an example of using of the offered adaptive observer the structure and algorithm of joint identification of the moment of inertia (parameter) and the torque of resistance (external disturbance) of mechanical load of dc electric drive model are obtained. Asymptotic stability of processes of joint identification of the parameter and external disturbance of drive model is proved. Simulation results of identification processes and their using for control system adaptation are shown on graphs of transition processes. Designed algorithm for the joint identification of parameter and external disturbance of plant provide adaptive stabilization of desirable dynamic properties of control system with adaptive observer.