Francis turbine electrohydraulic inlet guide vane control by artificial neural network 2 degree-of-freedom PID controller with actuator fault

Hydropower system has great attention due to the cheapest and simplest renewable power generation, available potential and environmental concern. Francis turbine has wide operating range compare to...

[1]  Zhou Kunxion.  Transient modeling of hydraulic electricity-generating system in water-machine-electricity coupling conditions , 2015 .

[2]  Jianyong Yao,et al.  Internal Leakage Fault Detection and Tolerant Control of Single-Rod Hydraulic Actuators , 2014 .

[3]  Beibei Xu,et al.  Nonlinear modeling and dynamic analysis of hydro-turbine governing system in the process of load rejection transient , 2015 .

[4]  Bikash Kr. Sarkar,et al.  Position Control of the Hydraulically Actuated Francis Turbine Inlet Guide Vane , 2017 .

[5]  Lixiang Zhang,et al.  Reconstruction of the complete characteristics of the hydro turbine based on inner energy loss , 2016 .

[6]  Bo Zhang,et al.  Embedded Hardware Artificial Neural Network Control for Global and Real-Time Imbalance Current Suppression of Parallel Connected IGBTs , 2020, IEEE Transactions on Industrial Electronics.

[7]  Bin Wang,et al.  Fuzzy generalised predictive control for a fractional-order nonlinear hydro-turbine regulating system , 2018 .

[8]  Jian Zhang,et al.  Stability analysis of hydro-turbine governing system including surge tanks under interconnected operation during small load disturbance , 2019, Renewable Energy.

[9]  F. Van De Meulebroeke,et al.  Hydro turbine model for system dynamic studies , 1994 .

[10]  Firas M. Tuaimah,et al.  Modeling of SVC Controller based on Adaptive PID Controller using Neural Networks , 2012 .

[11]  Hong-Bae Jun,et al.  Stability analysis of a hydro-turbine governing system considering inner energy losses , 2019, Renewable Energy.

[12]  Canbing Li,et al.  Robust fixed-time sliding mode control for fractional-order nonlinear hydro-turbine governing system , 2019, Renewable Energy.

[13]  Bin Wang,et al.  Takagi–Sugeno fuzzy generalised predictive control of a time-delay non-linear hydro-turbine governing system , 2019 .

[14]  João Viana da Fonseca Neto,et al.  On the design and analysis of structured-ANN for online PID-tuning to bulk resumption process in ore mining system , 2020, Neurocomputing.

[15]  Hamid Reza Karimi,et al.  A Novel Finite-Time Control for Nonstrict Feedback Saturated Nonlinear Systems With Tracking Error Constraint , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Ayman A. El-Badawy,et al.  Active control of variable geometry Francis Turbine , 2020 .

[17]  J. D. McCalley,et al.  Analysis of Very Low Frequency Oscillations in Hydro-Dominant Power Systems Using Multi-Unit Modeling , 2012, IEEE Transactions on Power Systems.

[18]  Muhannad Quwaider,et al.  Neural network model as Internet of Things congestion control using PID controller and immune-hill-climbing algorithm , 2020, Simul. Model. Pract. Theory.

[19]  Xiaohui Yuan,et al.  Nonlinear dynamic analysis and robust controller design for Francis hydraulic turbine regulating system with a straight-tube surge tank , 2017 .

[20]  Dipankar Sanyal,et al.  Active Power Control of the Francis Turbine System by Model-Free Adaptive Controller , 2020 .

[21]  Diyi Chen,et al.  Disturbance observer-based backstepping sliding mode fault-tolerant control for the hydro-turbine governing system with dead-zone input. , 2019, ISA transactions.

[22]  Jing Qian,et al.  The generalized Hamiltonian model for the shafting transient analysis of the hydro turbine generating sets , 2014 .

[23]  Kangkang Sun,et al.  Event-Triggered Robust Fuzzy Adaptive Finite-Time Control of Nonlinear Systems With Prescribed Performance , 2020, IEEE Transactions on Fuzzy Systems.

[24]  Wencheng Guo,et al.  Saturation characteristics for stability of hydro-turbine governing system with surge tank , 2019, Renewable Energy.

[25]  Alejandro Garces,et al.  Passivity-based control and stability analysis for hydro-turbine governing systems , 2019, Applied Mathematical Modelling.

[26]  Vikas Kumar,et al.  ANN based self tuned PID like adaptive controller design for high performance PMSM position control , 2014, Expert Syst. Appl..

[27]  Nand Kishor,et al.  Dynamic simulations of hydro turbine and its state estimation based LQ control , 2006 .

[28]  Jane E. Sargison,et al.  Modelling of Transient Behaviour in a Francis Turbine Power Plant , 2004 .

[29]  Chuanwen Jiang,et al.  PID controller parameters optimization of hydro-turbine governing systems using deterministic-chaotic-mutation evolutionary programming (DCMEP) , 2006 .

[30]  Vera Kurková,et al.  Kolmogorov's theorem and multilayer neural networks , 1992, Neural Networks.

[31]  Alireza Rahai,et al.  Prediction of bond strength of spliced steel bars in concrete using artificial neural network and fuzzy logic , 2012 .

[32]  S. Mookherjee,et al.  Approaching Servoclass Tracking Performance by a Proportional Valve-Controlled System , 2013, IEEE/ASME Transactions on Mechatronics.

[33]  Wencheng Guo,et al.  Hopf bifurcation control of hydro-turbine governing system with sloping ceiling tailrace tunnel using nonlinear state feedback , 2017 .

[34]  Xiangyu Wang,et al.  Hamiltonian analysis of a hydro-energy generation system in the transient of sudden load increasing , 2017 .

[35]  Debdoot Sain,et al.  Real-Time implementation and performance analysis of robust 2-DOF PID controller for Maglev system using pole search technique , 2019, J. Ind. Inf. Integr..