# Modeling and Speed Tuning of a PMSM with Presence of Fisure Using Dragonfly Algorithm
Indeed, since its synthesis is based on heuristic knowledge, linguistic description to perform a task and does not require a system model, the fuzzy logic control (FLC) idea is successfully applied to motor systems. The authors mentioned that the occurrence of failure may dramatically degrade the system performance and may even result in catastrophic system collapse. Therefore, in order to overcome this, they have designed a new fault tolerant control (FTC)-structure-based FLC to improve PMSM drive currents and speed controls during healthy and faulty conditions. The dynamic model of electromechanical systems with the presence of degradation in the proposed inertia presents highly non-linear behaviors, which means that tuning is relatively complicated for the characteristic parameters, which are tuned using a population-based optimization algorithm, Fuzzy Control, and spectral tools [7; 8; 9; 10]. In [11], the parameters of the 3-DOF PID controller are optimized by using the dragonfly algorithm (DA) for enhancing the system dynamics of a hybrid energy distributed power system subject to load and wind power variations. The algorithm is inspired from the static and dynamic swarming behavior of dragonflies, where the operation of DA is only dependent on the population size and the maximum iteration count. In [12], the DA was used to tune the controller parameters of the two-degrees-of-freedom PID for a multi-area power system. The performance of DA was evaluated in terms of tie-line power of control areas in the power system and the settling time of the deviations in frequency. The main contribution of the paper is the design of a control scheme for a PMSM with the presence of fissure in the rotor shaft, causing this and, according to the fracture dynamics, degradation as well. In this work, a detailed analysis is provided of the modeling and tuning of this nonlinear dynamic system, which contributes to a more accurate theory of the dynamic behavior of the PMSM. The proposed algorithm combines a linear PID controller and an optimal quadratic controller to regulate the velocity trajectory tracking. To define the convergence domain of the possible regulation gains in the dynamic model of the PMSM using the optimization dragonfly algorithm (DA) technique, a sensitivity analysis of the same is carried out, in order to limit the definition domain, minimize the evaluation time and help the convergence of the dynamic system. The control scheme of the PMSM is simple and robust and can operate within a very wide speed range. The rest of the document is organized as follows: Section 2 develops the dynamic model of PMSM with the presence of a rotor fissure. In Section 3, a presentation of the control scheme of the dynamic PMSM model is given. In Section 4, the control tuning procedure through the Dragonfly algorithm is presented. Section 5 describes the procedure for conducting a sensitivity analysis. In Section 6, the simulation of the dynamic system of the PMSM is carried out. Finally, Sections 7 and 8 present the results of the implementation and a discussion of the results, respectively.