Hardware-in-the-loop implementation of an unknown input observer for synchronous reluctance motor.

In this paper, we design a proportional integral observe for a nonlinear synchronous reluctance motor described by a Takagi-Sugeno multi-model. In this design, both states and unknown inputs are estimated simultaneously. First, the mathematical nonlinear model of the synchronous reluctance motor is established, then it transformed into a Takagi-Sugeno exact form by a simple polytopic transformation. In The second step, the proposed observer is designed to the obtained fuzzy system. Convergence conditions are expressed under a linear matrix inequality formulation using the second Lyapunov theorem, which guarantee a bounded error. Observer gains are obtained by solving a sum of constraints. For validation purposes, a hardware-in-the-loop implementation were carried out leading to results that clearly demonstrate the performance and effectiveness of the proposed technique.

A new rooted tree optimization algorithm for indirect power control of wind turbine based on a doubly-fed induction generator.

A new control strategy based on the root tree optimization (RTO) is presented in order to reduce the chattering phenomena in active and reactive powers, and to minimize the harmonic currents which appear mostly at the level of the rotor side converter (RSC), in a doubly-fed induction generator (DFIG). The root tree optimization is used to adjust the parameters (Kp,Ki) of PI controller (RTO-PI). Simulation results are presented to demonstrate the effectiveness of the new proposed technique. Besides, the system associated with this metaheuristic algorithm can effectively give better dynamic and steady performance. The results with the RTO-PI controller show more performances than the results compared with the classical PI.