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摘要
This paper designs a novel adaptive fractional-order PID (AFOPID) control of a permanent magnetic synchronous generator (PMSG)-based wind energy conversion system, which attempts to extract the maximum wind power by using a linear perturbation observer. The combinatorial effect of generator nonlinearities and parameter uncertainties, unmodelled dynamics, and stochastic wind speed variation is aggregated into a perturbation, which is then estimated in real time by a linear extended-state observer called high-gain state and perturbation observer. Besides, the perturbation estimate is used as an auxiliary control signal which is fully compensated by a fractional-order PID (FOPID) controller to achieve a globally robust control consistency, simple structure and high reliability, as well as an improved tracking performance compared to that of PID control. In addition, AFOPID does not require an accurate PMSG model while only the measurement of d-axis current and mechanical rotation speed is required, in which parameter is optimally tuned by particle swarm optimization. Four case studies are carried out, including step change of wind speed, low-turbulence stochastic wind speed, high-turbulence stochastic wind speed, and generator parameter uncertainties, respectively. Simulation results verify the effectiveness and superiority of AFOPID compared to that of PID, FOPID, and nonlinear control.
