Modeling and Speed Tuning of a PMSM with Presence of Fissure Using Dragonfly Algorithm

Abstract

This paper presents a robust trajectory tracking control for a Permanent Magnet Synchronous Motor (PMSM) with consideration a fault, parametric uncertainties and external disturbances by effectively integrating robust optimal linear quadratic control. One kind of fault is considered in the machine, particularly the presence of fissure rotor. The dynamic model of the PMSM with the presence of fissure presents highly non-linear behaviors, which means that tuning is quite complicated, which the tuning was chosen through swarm intelligence optimization (Dragonfly Algorithm). A sensitivity analysis is carried out, in order to limit the search range to minimize the evaluation time. This methodology was used to diminish these defects during motor operation. Simulation results show that the optimal linear quadratic control method has a robust fault-tolerant performance.

Neuroadaptive Robust Speed Control for PMSM Servo Drives with Rotor Failure

“…where L d is the d-axes stator inductance and L q represent the q-axes stator inductance, i d is the stator current in d-axes, i q represent the stator current in q-axes, V d is the stator voltage in d-axes and V q represent the stator voltage in q-axes, r s represent the stator resistance per phase, ω r is the rotor mechanical angular speed and λ m is the rotor flux. The differential equations that define the dynamics of the PMSM rotor with respect to angular velocity and the angular position (θ) of the rotor are determined as follows [1][2][3]9,10]:…”

“…Then, when there is a crack in the rotor, the fracture opens and closes due to the moment of inertia and the rotational effects of the rotor mass, which over time the rotor failure will behave as a weak fracture. [9,10,24]. The mathematical expression that defines the dynamic behavior of the fissure within the rotor can be described with the Paris equation, as follows [24,25].…”

“…where a is the fissure size, c is the proportional coefficient which depends on the type of rotor material, ∆K is the variation of the stress concentrator, n is the proportional exponent which depends on the type of rotor material and f is the fundamental rotor frequency. The stress intensity factor is defined as [10]:…”

“…where D is the root of rotor shaft diameter and d is the size of the cavity in the rotor shaft due to the fissure, which the smaller diameter of d is defined as a function of the variation in the length of the fissure as [9,10,26]:…”

“…Rotor failures have been studied by different groups of researchers. Classical control has been applied to deal with the presence of degradation problems, fault, and broken rotors in electromechanical systems, such as optimal linear quadratic regulator [9,10], sliding mode control [11], feedback linearization controller [12], and fuzzy logic control [13]. In [9] an optimal linear state feedback control scheme was designed using the optimal linear quadratic regulator technique, for a PMSM with rotor failure.…”