Finite-Time Chaos Control of a Complex Permanent Magnet Synchronous Motor System

This paper investigates the finite-time chaos control of a permanent magnet synchronous motor system with complex variables. Based on the finite-time stability theory, two control strategies are proposed to realize stabilization of the complex permanent magnet synchronous motor system in a finite time. Two numerical simulations have been conducted to demonstrate the validity and feasibility of the theoretical analysis

Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM) drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method

Chaotification of permanent-magnet synchronous motor drives using time-delay feedback

Recent research has shown that chaos can actually be useful under certain circumstances, and there is growing interest in utilizing the very nature of chaos. Thus, a controllable chaotic motor drive, namely chaotifying a motor drive, is highly desired for practical engineering systems. This paper firstly proposes and implements a time-delay feedback method to chaotify a practical permanent-magnet synchronous motor (PMSM) drive. Based on the current-fed model and field-oriented control, the corresponding system dynamics will be approximated by first-order differential equations. Hence, the electromechanical torque will be adjusted according to the time-delay speed feedback. Consequently, chaotic motion can be achieved by tuning the feedback gain of the torque controller. Moreover, the resulted chaotic motion is easily controllable in the sense that the rotor speed boundary can be controlled precisely by the value of the speed ratio. This controllable chaotic PMSM drive potentially offers some special applications desiring chaotic motion such as fluid mixing and surface grinding. Theoretical analysis, computer simulation as well as experimental results will be given to verify the proposed method of chaotification.published_or_final_versio

Application of Vector Control to Permanent Magnet Synchronous Motors Using Chaos Control

This paper presents the idea of vector control for permanent magnet synchronous motor (PMSM) based on chaos theorem, using chaos controller. PMSM will demonstrate chaotic phenomena when its parameters fall into a certain area. To achieve this aim, the sub-system of controller has been designed by considering block diagram structure of vector control for PMSM and by applying the setting of Lyapunov exponents method. Also, asymptotical stability of closed loop system with given controller is shown, using the direct Lyapunov method. The performance of designed controller in chaotic mode is compared with conventional vector control methods. Also, the normal mode for PMSM is considered and the performance of controller is compared. Simulation results indicate that not only does this controller eliminate the chaos in chaotic mode and have good performance but also is able to control the system in normal mode by using almost the smaller control signal effort

Linear robust output−feedback control for permanent−magnet synchronous motors with unknown load

International audienceWe solve the problem of set-point (respectively, tracking) control of a permanent-magnet synchronous motor via linear time-invariant (respectively, time varying) control. Our control approach is based on the physical properties of the machine: inherent stability and robustness to external disturbances. Our analysis is carried out under mild conditions, using cascaded systems theory. For all cases: constant operating point, trajectory tracking, and with known and unknown load, we show uniform global asymptotic stability of the closed-loop system with a linear controller that uses only velocity measurements. Furthermore, we explore natural extensions of our results to improve robustness with respect to external disturbances and parametric uncertainties

Design of Permanent Magnets to Avoid Chaos in PM Synchronous Machines

This paper analyzes the effect of permanent magnets (PMs) on the occurrence of chaos in PM synchronous machines (PMSMs). Based on the newly derived nonlinear system equation, the bifurcation analysis shows that the sizing of PMs significantly determines the stability of PMSMs. Hopf bifurcation and chaos may even occur in the PMSMs if the PMs are not properly sized. Experimental results of two practical PMSMs are provided to support the theoretical analysis.published_or_final_versio

Nonlinear Time-Frequency Control of Permanent Magnet Electrical Machines

Permanent magnet (PM) electrical machines have been widely adopted in industrial applications due to their advantages such as easy to control, compact in size, low in power loss, and fast in response, to name only a few. Contemporary control methods specifically designed for the control of PM electrical machines only focus on controlling their time-domain behaviors while completely ignored their frequency-domain characteristics. Hence, when a PM electrical machine is highly nonlinear, none of them performs well. To make up for the drawback and hence improve the performance of PM electrical machines under high nonlinearity, the novel nonlinear time-frequency control concept is adopted to develop viable nonlinear control schemes for PM electrical machines. In this research, three nonlinear time-frequency control schemes are developed for the speed and position control of PM brushed DC motors, speed and position control of PM synchronous motors, and chaos suppression of PM synchronous motors, respectively. The most significant feature of the demonstrated control schemes are their ability in generating a proper control effort that controls the system response in both the time and frequency domains. Simulation and experiment results have verified the effectiveness and superiority of the presented control schemes. The nonlinear time-frequency control scheme is therefore believed to be suitable for PM electrical machine control and is expected to have a positive impact on the broader application of PM electrical machines

Nonlinear Dynamic Surface Control of Chaos in Permanent Magnet Synchronous Motor Based on the Minimum Weights of RBF Neural Network

This paper is concerned with the problem of the nonlinear dynamic surface control (DSC) of chaos based on the minimum weights of RBF neural network for the permanent magnet synchronous motor system (PMSM) wherein the unknown parameters, disturbances, and chaos are presented. RBF neural network is used to approximate the nonlinearities and an adaptive law is employed to estimate unknown parameters. Then, a simple and effective controller is designed by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed controller is testified through simulation results

Design of permanent magnets to avoid chaos in doubly salient PM machines

This paper analyzes the effect of permanent magnets (PMs) on the formation of chaos in doubly salient PM (DSPM) machines. Based on the newly derived nonlinear system dynamical equation, the corresponding Poincaré map and bifurcation diagram show that the sizing of PMs significantly affects the stability of DSPM machines. Chaos may be resulted if the PMs are not properly designed. Both computer simulations and experimental results are provided to support the theoretical derivation.published_or_final_versio