Application of model free active disturbance rejection controller in nuclear reactor power control

2021 ◽  
Vol 140 ◽  
pp. 103907
Author(s):  
Aodi Sun ◽  
Pu Songmao ◽  
Zhengxi He ◽  
Kai Xiao ◽  
Peiwei Sun ◽  
...  
2022 ◽  
Vol 169 ◽  
pp. 108931
Author(s):  
Jiaoshen Xu ◽  
Hui Tang ◽  
Xin Wang ◽  
Ge Qin ◽  
Xin Jin ◽  
...  

Author(s):  
H. Zarabadipour ◽  
H. Emadi

The power control system of a nuclear reactor is one of the key systems that concern the safe operation of the plant. Much attention is paid to the power control systems’ performance of nuclear reactor in engineering. The goal of this paper is apply balance model reductionto derive reduced order model and then design the reduced optimal controller for nuclear reactor power system.The simulation results with reduced-order model and with optimized controller show that the proposed technique is improved .


2020 ◽  
pp. 002029402091717 ◽  
Author(s):  
Wameedh Riyadh Abdul-Adheem ◽  
Ibraheem Kasim Ibraheem ◽  
Amjad J Humaidi ◽  
Ahmad Taher Azar

Traditional input–output feedback linearization requires full knowledge of system dynamics and assumes no disturbance at the input channel and no system’s uncertainties. In this paper, a model-free active input–output feedback linearization technique based on an improved active disturbance rejection control paradigm is proposed to design feedback linearization control law for a generalized nonlinear system with a known relative degree. The linearization control law is composed of a scaled generalized disturbance estimated by an improved nonlinear extended state observer with saturation-like behavior and the nominal control signal produced by an improved nonlinear state error feedback. The proposed active input–output feedback linearization cancels in real-time fashion the generalized disturbances which represent all the unwanted dynamics, exogenous disturbances, and system uncertainties and transforms the system into a chain of integrators up to the relative degree of the system, which is the only information required about the nonlinear system. Stability analysis has been conducted based on the Lyapunov functions and revealed the convergence of the improved nonlinear extended state observer and the asymptotic stability of the closed-loop system. Verification of the outcomes has been achieved by applying the proposed active input–output feedback linearization technique on the single-link flexible joint manipulator. The simulations results validated the effectiveness of the proposed active input–output feedback linearization tool based on improved active disturbance rejection control as compared to the conventional active disturbance rejection control–based active input–output feedback linearization and the traditional input–output feedback linearization techniques.


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