A high performance adaptive parallel distributed compensator for induction machine drives

An adaptive parallel distributed compensator (APDC) using Takagi-Sugeno fuzzy systems for indirect field oriented (IFO) induction machines is proposed. An on-line method is used to adjust the parameters of a Takagi-Sugeno identifier model to match the behavior of IFO induction machine drive system. Then, using the certainty equivalence principle, the parameters of the Takagi-Sugeno identifier model are employed in a standard control design method for the standard parallel distributed compensator to provide a global asymptotically stable equilibrium for the closed loop IFO drive system. In this way, identifier does not need to have any initial knowledge about the IFO drive system and as the identifier becomes more accurate, the controller parameters of the parallel distributed compensator will be adjusted, and if the identifier succeeds in its task, the controller will too. The proposed controller is simulated for a 5 hp induction machine drive system. The comparison of the standard PI and APDC is presented by simulation as well. These results prove that the proposed controller is robust to load changes and system disturbances and can also follow different command trajectories very well without any re-tuning of the controller