Output tracking for nonlinear systems subject to unmodeled sluggish actuator dynamics via model-based extended state observer

2021 ◽  
Author(s):  
Minjie Zhang ◽  
Lei Yang ◽  
Yanze Hou ◽  
Maopeng Ran ◽  
Shen Zhang
Keyword(s):  
Nonlinear Systems ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Actuator Dynamics ◽  
Output Tracking ◽  
Model Based

Characteristic model–based adaptive controller with discrete extended state observer for servo systems

2017 ◽  
Vol 231 (4) ◽  
pp. 259-270 ◽  
Author(s):  
Xiang Wang ◽  
Yifei Wu ◽  
Enze Zhang ◽  
Jian Guo ◽  
Qingwei Chen
Keyword(s):  
Discrete Time ◽  
Adaptive Controller ◽  
State Observer ◽  
Lyapunov Theory ◽  
Extended State Observer ◽  
Recursive Least Squares ◽  
Extended State ◽  
Servo Systems ◽  
Characteristic Model ◽  
Model Based

Inertia variations and torque disturbances, most often considered as two of the major uncertainties in servo systems, highly affect the control performance. This article presents a characteristic model–based adaptive controller in the presence of large-range load inertia variations. A discrete-time characteristic model of the servo system, which has more advantages in describing time-varying dynamics, is established. The parameters of characteristic model are identified by a recursive least squares algorithm. To restrain the identification error and load torque disturbances, a discrete extended state observer is newly designed for the discrete-time system. Both the convergence of discrete extended state observer and the stability of closed-loop system are verified by the Lyapunov theory. Finally, simulation and experimental results demonstrate that the proposed controller provides better performance than the fuzzy proportional integral controller in terms of adaptability and robustness.

Sign in / Sign up

Export Citation Format

Share Document