Active disturbance rejection control for nonlinear fractional-order systems

2015 ◽  
Vol 26 (4) ◽  
pp. 876-892 ◽  
Author(s):  
Zhe Gao
Keyword(s):  
Fractional Order ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Fractional Order Systems ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

scholarly journals Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

2022 ◽  
Vol 70 (3) ◽  
pp. 5133-5142
Author(s):  
Ibrahim M. Mehedi ◽  
Rachid Mansouri ◽  
Ubaid M. Al-Saggaf ◽  
Ahmed I. M. Iskanderani ◽  
Maamar Bettayeb ◽  
...  
Keyword(s):  
Fractional Order ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Joint System ◽  
Flexible Joint ◽  
Order Linear ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

scholarly journals Fractional-Order PID and Active Disturbance Rejection Control with Tuning Parameter Optimization for Induction Heating

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bingyu Li ◽  
Jining Guo ◽  
Ying Fu
Keyword(s):  
Fractional Order ◽  
Temperature Control ◽  
Induction Heating ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Heating Systems ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Fractional Order Pid ◽  
Control Accuracy

Induction heating systems are characterized by model uncertainty, nonlinearity, and external disturbances, and the control accuracy of the system directly affects the performance of the heated workpiece. In order to improve the temperature control accuracy and anti-interference performance of induction heating systems, this paper proposes a composite control strategy combining fractional-order PID (FOPID) and active disturbance rejection control (ADRC). Meanwhile, for the problem of too many controller tuning parameters, an improved quantum behavior particle swarm optimization (QPSO) algorithm is used to transform the nine parameters to be tuned in fractional-order PID active disturbance rejection control (FOPID-ADRC) into a minimization value optimization problem for solving. The simulation results show that the FOPID-ADRC controller improves the anti-interference capability and control accuracy of the temperature control system, and the improved QPSO algorithm has better global search capability and local optimal adaptation value.

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