PMSG CONSTANT POWER CONTROL BASED ON RBF-PID AND SENSITIVE VARIABLE SLIDING MODE REACHING LAW
A variable pitch control strategy based on RBF neural network for real-time online adjustment of PID parameters is proposed to address the issue of unstable output power and impact on power quality of offshore direct drive permanent magnet wind turbines when wind speed exceeds rated wind speed.The self-learning ability of the neural network is utilized to continuously optimize internal parameters,making the system more adaptable to nonlinearity and time-varying.In order to further improve the response speed of pitch angle change and the stability of output power,a sensitive variable exponential reaching law sliding mode controller is designed and embedded into the generator side speed loop.The sensitive variable can improve the Rate of convergence and anti chattering ability of the system.Build simulation modules for various parts of the direct drive permanent magnet wind turbine generator on Matlab/Simulink and conduct comparative experiments.The results show that the pitch control strategy based on RBF-PID and sensitive variable sliding mode approach law has a faster response to pitch angle changes,more stable output power,and a oscillation rate of only 0.4% compared to before improvement,achieving the expected control effect.
wind turbinespower qualityneural networksensitive variablessliding mode control
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