Dynamic Analysis and Control of a Permanent Magnet Synchronous Motor With External Perturbation

Abstract

Chaotic motion and chaos control of a permanent magnet synchronous motor (PMSM) are studied in this paper. The dynamics of chaotic PMSM with load vibration perturbation is presented and its complex dynamic characteristics are analyzed by using bifurcation diagrams, Lyapunov exponents, and phase portraits. Furthermore, an adaptive neural sliding mode control is addressed to suppress chaos oscillations for the PMSM. The neural network approximation is applied in the controller to emulate of the load perturbation. Simulation results show that the proposed control scheme can eliminate the chaos and make the system achieve stable states even with the existence of unknown load vibration disturbance.

Dynamic Behaviors and Mechanisms of Permanent Magnet Synchronous Motor with Excitation

“…Rasoolzadeh and Tavazoei [6] discussed the dynamic behaviors of PMSM with external excitation and analyzed the effect of excitation angle-frequency on the dynamic behaviors by using bifurcation diagram. Wang et al [7] analyzed the dynamic response of PMSM under FOC control and obtained different attractors with the change of single parameter. In reference [8], the parameter region is divided into the chaotic area and nonchaotic area by a lot of simulation results, and the maximum torque output of the stable region is estimated based on the nonchaotic area.…”

Permanent magnet synchronous motor: chaos control using single controller, synchronization and circuit implementation

“…Chaotic behavior of the PMSM is undesirable since it can destroy the stabilization of the motor and even induce the drive system to collapse Ref. [33]. Consequently, chaos control with the aim of suppressing the undesired chaotic behavior of PMSM has attracted increasing attention in order to further improve the performance of the system in the industrial and academic community [6,22,35].…”

“…Chaos control in PMSM has been implemented with several methods. Feedback control method [2,12,14], adaptive fuzzy control [5,21,37,38], simple sliding mode adaptive control [7,23], adaptive neural sliding mode control [33], optimal Lyapunov exponents' placement [1], passive control [25], impulsive control [6,10] and finite-time stability theory [27] were used for the control of chaotic behavior in PMSM. However, the methods mentioned above have some shortcomings.…”

Spiking oscillations and multistability in nonsmooth‐air‐gap brushless direct current motor: Analysis, circuit validation and chaos control

“…Extensive efforts have been done to investigate the dynamics of electronic motor drive systems 1‐4 during the past three decades. The focus on such systems is first due to the fact that they are key to the growth of any modern society and they can be found in steel rolling mills, drilling machines, railway traction, industrial robots, electrical vehicles, aerospace and in most household items and office equipment 1‐3 .…”

“…The focus on such systems is first due to the fact that they are key to the growth of any modern society and they can be found in steel rolling mills, drilling machines, railway traction, industrial robots, electrical vehicles, aerospace and in most household items and office equipment 1‐3 . Second, the dynamical behaviors such as chaotic behavior can destabilize the electronic motor drive systems 3,4 . Thereafter, many research works looking for the chaotic behaviors have been reported in various kinds of electronic motor drive systems: Hybrid step motor drive, 5 induction motor drive, 6 permanent‐magnet synchronous motor drive, 7‐9 voltage‐mode and current‐mode direct current motor drives, 10,11 switched reluctance motor drive, 1 2 synchronous reluctance motor drive, 13 and brushless direct current motor (BLDCM) drive 14 …”