A Novel Design of PI Current Controller for PMSG-based Wind Turbine Considering Transient Performance Specifications and Control Saturation


This paper presents a novel design process of decoupled PI current controller for permanent magnet synchronous generator (PMSG)-based wind turbines feeding a grid-tied inverter through back-to-back converter. Specifically, the design methodology consists of combining disturbance observer-based control (DOBC) with feedback linearization (FBL) technique to ensure nominal transient performance recovery under model uncertainty. By simplifying the DOBC under the feedback linearizing control, it is shown that the composite controller reduces to a decoupled PI current controller plus an additional term that has the main role of recovering the nominal transient performance of the feedback linearization, especially under step changes in the reference. Additionally, an anti windup compensator arises naturally into the controller when considering the control input saturation to design the  DOBC. This permits to remove the effect of the saturation blocks required to limit the control input. The proposed control scheme is implemented and validated through experimentation conducted on 22-pole, 5 kW PMSG. The results revealed that the proposed technique can successfully achieve nominal performance recovery under model uncertainty as well as improved transient performances under control saturation.


  1. Anti-windup scheme
  2. Disturbance observer
  3. Nominal performance recovery
  4. Permanent magnet synchronous generator (PMSG)
  5. PI controller
  6. Renewable energy
  7. Wind energy conversion system



 Fig. 1. Configuration of a direct-drive PMSG-based WECS connected

to the host grid.



Fig. 2. System’s response under the composite controller consisting of the feedback controller (13) and the PI-DO (34)–(37). The controller was tested experimentally using the block diagram of Fig. 3. Specifically, the PI-DO (34)–(37) was evaluated with and without the consideration of the reference jump .

Fig. 3. System’s response under the composite controller consisting of the feedback controller (13) and the DOBC (25). The controller was tested experimentally using the block diagram depicted in Fig. 2.

Fig. 4. System’s response under a conventional PI current controller [17].

Fig. 5. Performance evaluation of the proposed PI-DO under model uncertainty.

Fig. 6. Experimental results: Performance testing of the proposed PI current controller under MPPT algorithm, with id (2 A/div), iq (4 A/div), ia (10 A/div), ws (5 [m/s]/div), iga (6 A/div), r (50 [rpm/min]/div), and time (400 ms/div)


This paper has presented a novel design of decoupled PI controller to enhance the transient performance for the current control of PMSG-based wind turbine. The proposed controller technique was established by combining a DOBC with feedback linearizing control law. It turns out that the composite controller has a decoupled PI-like structure plus two additional parts. The first part is basically an anti-windup compensator, while the second part uses the reference jump information to cancels out the effect of the sudden step changes in the power demand on the transient response. This modification of the decoupled PI controller permits to guarantee zero steady-state error without sacrificing the nominal transient performance specified by the state feedback controller. This salient feature cannot be achieved under the existing decoupled PI controller, particularly when the model parameters are not accurate. Experimental tests have been performed, and the results support the use of the reference jump information to improve the transient performance under the decoupled PI controller. Therefore, the proposed approach provides practitioners with an alternate method in designing a robust decoupled PI current controller for PMSG-based wind energy conversion system.


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[3] S. Benelghali, M. E. H. Benbouzid, J. F. Charpentier, T. Ahmed-Ali, and I. Munteanu, “Experimental validation of a marine current turbine simulator: Application to a permanent magnet synchronous generator based system second-order sliding mode control,” IEEE Trans. Ind. Electron, vol. 58, no. 1, pp. 118–126, Jan 2011.

[4] C. Wei, Z. Zhang, W. Qiao, and L. Qu, “An adaptive network-based reinforcement learning method for MPPT control of PMSG wind energy conversion systems,” IEEE Trans. Power Electron., vol. 31, no. 11, pp. 7837–7848, Nov 2016.

[5] H. M. Yassin, H. H. Hanafy, and M. M. Hallouda, “Enhancement low-voltage ride through capability of permanent magnet synchronous generator-based wind turbines using interval type-2 fuzzy control,” IET Renew. Power Gen., vol. 10, no. 3, pp. 339–348, 2016.

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