Disturbance Observer based Fractional-order Integral Sliding Mode Frequency Control Strategy for Interconnected Power System

Author(s):  
Fan Yang ◽  
Xinyi Shao ◽  
S. M. Muyeen ◽  
Dongdong Li ◽  
Shunfu Lin ◽  
...  
Author(s):  
Zebin Yang ◽  
Kun Wang ◽  
Xiaodong Sun ◽  
Xiaoting Ye

In order to improve the capability of load disturbance resistance of vector control system for a bearingless induction motor, a control strategy of the bearingless induction motor based on sliding mode speed controller and load torque observer is proposed. The control strategy uses fractional integral of velocity error and designs the nonlinear integral order sliding mode surface, and then a new bearingless induction motor speed control system is constructed. The extended sliding mode observer is designed with the rotor position, rotational speed and load torque as the observation object. The low-pass filter is used to weaken the high-frequency chattering of the sliding mode control to improve the accuracy of the observation, and the load torque observation value is compensated to the fractional-order integral sliding mode speed controller. The simulation and experimental results show that the proposed scheme achieves accurate and fast tracking of the load torque, effectively suppresses the chattering and improves the robustness of the system. The control system improves the resistance capacity against load disturbance and has better dynamic performance.


Author(s):  
Xiaocong He ◽  
Lingfei Xiao

Abstract This paper presents a robust fault identification scheme based on fractional-order integral sliding mode observer (FOISMO) for turbofan engine sensors with uncertainties. The equilibrium manifold expansion (EME) model is introduced due to its simplicity and accuracy for nonlinear system. A fractional-order integral sliding mode observer is designed to reconstruct faults on sensors, in which the fractional-order integral sliding surface guarantees the fast convergence of reconstruction. The observer parameters is selected according to L2 gain theory in order to minimize the effect of uncertainties on the fault reconstruction signal. Simulations in Matlab/Simulink show high reconstruction accuracy of the proposed method despite the present of uncertainties.


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