J.X. Xu

Design of a Plug-In Repetitive Control Scheme for Eliminating Supply-Side Current Harmonics of Three-Phase PWM Boost Rectifiers Under Generalized Supply Voltage Conditions

This paper presents a digital repetitive control (RC) scheme to minimize the even-order harmonics at the dc link voltage and odd-order harmonics in the line-side currents under distorted and unbalanced supply voltage conditions. The proposed current control scheme consists of a conventional PI and a plug-in repetitive controller. On the basis of the mathematical model of the three-phase pulsewidth-modulated (PWM) boost rectifier under the generalized supply voltage conditions, the control task is divided into: 1) dc-link voltage harmonics control and 2) line-side current harmonics control . In the voltage harmonics control scheme, a reference current calculation algorithm has been derived accordingly to ensure that the dc link voltage is maintained constant at the demanded value and the supply-side power factor is kept close to unity. In the line-side current harmonics control scheme, a plug-in repetitive controller is designed to achieve low total harmonic distortion (THD) line-side currents of the three-phase PWM boost rectifier. The experimental test results obtained from a 1.6-kVA laboratory-based PWM rectifier confirm that the proposed control scheme can reduce the line-side current THD from 16.63% to 4.70%, and improve the dc-link voltage tracking accuracy substantially over the conventional PI-based controller.

Speed ripple minimization in PM synchronous motor using iterative learning control

Permanent-magnet synchronous motor (PMSM) drives are widely used for high-performance industrial servo applications where torque smoothness is an essential requirement. However, one disadvantage of PMSM is parasitic torque pulsations, which induce speed oscillation that deteriorates the drive performance particularly at low-speeds. To suppress these speed ripples, two iterative learning control (ILC) schemes implemented in the time domain and frequency domain respectively are proposed in this paper. Although a conventional proportional-integral (PI) speed controller does suppress speed ripples to a certain extent, it is not adequate for many high performance applications. Thus, the proposed plug-in ILC controller is applied in conjunction with a PI speed controller to further reduce the periodic speed ripples. Experimental verification of the two schemes is carried out, and test results obtained demonstrate that the scheme implemented in frequency domain has better performance in reducing speed ripples than that implemented in time domain because of the elimination of forgetting factor that is indispensable for robustness in time domain learning method.

Iterative learning-based high-performance current controller for switched reluctance motors

Switched reluctance motors (SRMs) are being considered for variable speed drive applications due to their simple construction and fault-tolerant power-electronic converter configuration. However, inherent torque ripple and the consequent vibration and acoustic noise act against their cause. Most researchers have proposed a cascaded torque control structure for its well-known advantages. In a cascaded control structure, accurate torque control requires accurate current tracking by the inner current controller. As SRM operates in magnetic saturation, the system is highly nonlinear from the control point of view. Developing an accurate current tracking controller for such a nonlinear system is a big challenge. Additionally, the controller should be robust to model inaccuracy, as SRM modeling is very tedious and prone to error. In this paper, we have reviewed various current controllers reported in the literature and discussed their merits and demerits. Subsequently, we have proposed and implemented a novel high-performance current controller based on iterative learning, which shows improved current tracking without the need for an accurate model. Experimental results provided for a 1-hp, 8/6-pole SRM, demonstrate the effectiveness of our proposed scheme.

Analysis of the Instantaneous Power Flow for Three-Phase PWM Boost Rectifier Under Unbalanced Supply Voltage Conditions

This paper proposes the analysis of the instantaneous power flow of three-phase pulse-width modulation (PWM) boost rectifier under unbalanced supply voltage conditions. An analytical expression for the instantaneous output power has been derived, which provides the link between the output dc link voltage and the instantaneous output power. A direct relationship between the dc link voltage ripples and the second harmonic component in the instantaneous output power has been established. Based on the input and output instantaneous power analytical expressions provided, the presence of the odd order harmonic components in the ac line currents can be explained. A simple cascaded PI control scheme has been developed for the dc output voltage control. The controller ensures that the dc link voltage is maintained constant and the supply side power factor is kept close to unity under the unbalanced supply voltage operating conditions. Simulation and experimental test results are provided on a 1.6-kVA laboratory-based PWM rectifier to validate the proposed analysis and control scheme.

DC Link Voltage and Supply-Side Current HarmonicsMinimization of Three Phase PWM BoostRectifiers Using Frequency Domain BasedRepetitive Current Controllers

This paper presents a digital plug-in frequency domain based repetitive control scheme for minimizing the odd order harmonics in the supply line side currents of the three phase pulsewidth modulation (PWM) boost rectifier under the distorted and unbalanced supply voltage conditions. Based on the mathematical model of the three-phase PWM boost rectifier under the generalized supply voltage conditions, the control task is divided into: (a) dc-link voltage harmonics control and (b)supply line side current harmonics control. The proposed plug-in repetitive controller together with the conventional PI controller is designed to achieve supply line side currents with low total harmonic distortion (THD) for the three phase PWM boost rectifier. The repetitive control learning algorithm is implemented in the frequency domain by means of Fourier series approximation, instead of commonly used time domain based scheme, and provides the flexibility of choosing different learning gains and phase angle delay compensations individually for each harmonic component. The experimental test results obtained from a 1.6 kVA laboratory based PWM rectifier confirm that the THD of the supply line side currents can be reduced from 21.09% to 4.12% with the plug-in frequency domain based repetitive current controllers.

Torque ripple minimization in PM synchronous motor using iterative learning control

Permanent magnet synchronous motor (PMSM) drives are increasingly used in high-performance motion control applications where smooth torque is an essential requirement. However, presence of the air gap flux harmonics gives rise to undesirable torque pulsations. These torque pulsations result in performance deterioration in high-performance drive applications. In this paper, we present a systematic way to design and implement a new instantaneous torque controller using discrete iterative learning control (ILC) scheme with the objective of achieving torque ripple minimization. In the proposed scheme, the ILC-based dynamic torque controller compares the desired and the instantaneous motor torques and generates the reference q-axis current (i/sub qs_ref/) that is required to produce ripple-free torque. The instantaneous motor torque is estimated by using an estimator based on MRAS technique. The proposed ILC torque controller is simple to implement from a computational point of view. The effectiveness of the proposed torque controller is demonstrated through computer simulation studies and results obtained verify the effectiveness of the proposed scheme.

Fuzzy and neural controllers for dynamic systems: an overview

In this paper various trends in the area of intelligent control have been discussed. A brief account of the available control structures employing fuzzy logic and neural networks have been given. Some of these controller modules and their modified forms have been tested by the authors over a period of time on different systems. Some of them have been discussed and the results have been presented.

Application of Spatial Iterative Learning Control for Direct Torque Control of Switched Reluctance Motor Drive

In this paper, a novel direct torque controller for switched reluctance motor (SRM) is proposed using spatial iterative learning control (ILC). SRM magnetization characteristics are highly non-linear, and torque is a complex and coupled function of phase current and rotor position. Direct torque control (DTC) scheme avoids the complexity of torque-to- current conversion as required in indirect torque control scheme. Traditional DTC scheme uses a hysteresis controller and leads to large amount of torque ripples when implemented using a digital controller. Advanced non-linear control methods can be used to improve the performance of DTC in SRM. However, such methods are often too complex for real-time implementation or require an accurate model of SRM magnetization characteristics. As shown here, ILC only uses a linearized magnetization characteristics and a simple learning law to obtain the desired control signal. An ILC based DTC scheme for SRM torque control for constant motor torque, has been developed and experimentally verified on a 1-hp, 4-phase SRM. Experimental results show the effectiveness of the proposed scheme in terms of average torque control and ripple minimization.

Periodic torque ripples minimization in PMSM using learning variable structure control based on a torque observer

PM synchronous motor drives are widely used for high-performance industrial servo applications where torque smoothness is an essential requirement. However, parasitic torque pulsations do exist in PMSM drive due to non-perfect sinusoidal flux distribution, cogging torque and current measurement errors. A consequence of these torque ripples is speed oscillation that deteriorates the drive performance particularly at low speeds. In this paper, we propose a simple plug-in learning variable structure control (LVSC) scheme for generating a compensation reference current to improve the steady-state torque and hence the speed responses. A torque observer is designed to estimate the instantaneous motor torque, which can be used as the feedback of the proposed LVSC scheme. Extensive experimental investigations have been carried out in order to evaluate the performance of the scheme. Test results obtained demonstrate the effectiveness of the proposed control scheme in reducing torque ripples significantly.

Torque ripple minimization in PM synchronous motors an iterative learning control approach

Permanent magnet synchronous motor (PMSM) drives are widely used for high-performance applications where torque smoothness is an essential requirement. Parasitic torque pulsations in PMSM are generated due to harmonics in the stator flux linkage, cogging, current offsets etc. This paper describes a new instantaneous torque control scheme-iterative learning control (ILC), for torque ripple minimization. The proposed scheme has the advantage that torque ripples produced by the nonsinusoidal flux distribution is periodic in nature and therefore can be eliminated. This scheme is based on a dynamic torque controller and the conventional current controllers to minimize torque ripples. The dynamic torque controller compares the desired motor torque with the instantaneous motor torque, and generates the reference current (i/sub q-ref/) iteratively from cycle to cycle so as to reduce the torque error. The effectiveness of the proposed ILC scheme for torque ripple minimization is evaluated through simulation studies. Results obtained show that torque ripples can be significantly reduced using the proposed ILC scheme.