Deadbeat Control Research Articles

High-Dynamic Four-Quadrant Speed Adjustment of Switched Reluctance Machine With Torque Predictive Control

This article proposes a four-quadrant operation strategy of the switched reluctance machine (SRM) for the high-dynamic speed control, and the core of the strategy is a PWM-based predictive control method with the online adaptive phase excitation. The predictive control method is composed of the model predictive control (MPC) and deadbeat predictive control (DPC). The MPC is applied in the commutation region and the DPC is used to calculate the control signal for the single-phase excitation. With the proposed control method, the applicable operation range of the predictive control is extended to the braking torque region, and the four-quadrant operation of the SRM for the high-dynamic speed adjustment application is realized. The performances of the proposed control method are evaluated by detailed simulations and experiments under different conditions, and its superiority is demonstrated by comparing with other typical control methods.

Flying‐inductor‐cell based inverters for single‐phase transformerless PV applications

The application of the general flying-inductor (FI) cell in two novel transformerless photo-voltaic (PV) inverters are proposed and investigated. The simultaneous step up and down ability is possible with both topologies, while a high conversion efficiency and a high-quality AC current are achieved. The leakage current problem, which is a main concern with the transformerless PV inverters, is also considered. One of the proposed topologies presents a higher efficiency, while the other one provides the high quality of injected current with the lowest number active switches. The current control, especially at transition modes of operation is highly improved by utilizing a fast response dead-beat control scheme. The working principles of the proposed converters are explained in details and 0.88-kW experimental prototypes are implemented to confirm the theoretical achievements. Finally, a comparison with other existing topologies has been investigated for better clarification of the advantages and disadvantages of the proposed inverters.

Hybrid Active Power Filter for Power Quality Improvement

A Deadbeat current controller for an LC-coupling hybrid active power filter is proposed, which can track with the reference compensation current with low steady- state error and fast dynamic response. Moreover, it can lead Hybrid Active power Filter to be operating at a fixed switching frequency with low output current ripples, thus reducing the size of the filtering circuit. The stability issue and parameter design of the proposed deadbeat current controller are analyzed and discussed. Finally, the compensating performance of the deadbeat current controller for the Hybrid Active Power Filter (LC-HAPF) is verified by simulation compared with the conventional hysteresis bandwidth modulation control, the proportional-integral (PI) control, and the proportional multi-resonant control for the LC-HAPF, which shows its effectiveness and superior compensating performances.

Model predictive control of three-phase voltage-source converters with improved tracking performance

The conventional finite control set-model predictive control (FCS-MPC) has not been completely embraced by the power industry because of large tracking errors and the high required sampling frequency. Therefore, the double-vector-based model predictive control (DVB-MPC), which enfolds the deadbeat control (DBC) theory, has gradually crept into researchers’ horizons in recent years. In the universal DVB-MPC (UDVB-MPC) scheme, selecting two operation vectors in a single sector is a major obstacle to achieving satisfactory tracking performance. There is still a biggish error between the synthesized output voltage and the reference value. To alleviate this issue, this paper proposes an improved double-vector-based model predictive control (IDVB-MPC) scheme. The tracking errors are reduced dramatically by adding two extra vectors in adjacent sectors to the candidate set and dividing a sector into eight zones. Then the power fluctuation is reduced and the grid-connected current quality is improved. To verify the effectiveness of the proposed scheme, the simulation and experiment comparisons between UDVB-MPC and IDVB-MPC are carried out. The results show that IDVB-MPC reduces the quantitative tracking errors, the THD of the output currents, and the quantitative active power ripple by about 50%, 20%, and 35% with UDVB-MPC as a benchmark, respectively.

Generic predictive model calibration for PMSMs with different topologies

The main difficulty in designing predictive controllers for permanent magnet motors with different topologies is the control of the additional current subspaces. The frequency of current components in these additional subspaces (harmonic subspaces and zero-sequence loop/subspaces) is several times the fundamental current frequency. Moreover, the inner voltage source would vary with operation conditions, and there are also different views about the causes of inner voltage sources. This paper analyses the inner voltage sources in these additional current subspaces for permanent magnet motors with different drive topologies using simulation and experiment. Based on the results of the simulations and experiments, we analyze the sources and characteristics of the inner voltage sources and provide a predictive model calibration method for the components in these additional subspaces. Finally, the deadbeat current control scheme based on calibrated look-up table is designed and verified.

Deadbeat two-vector model predictive current control for open-winding primary permanent-magnet linear motor

The structure of open-winding motor fed by the dual-inverter can increase the winding terminal voltage of the primary permanent-magnet linear motor (PPMLM). So, it is an effective method to improve the thrust performance of the PPMLM. Based on the detailed derivation of the mathematical model of the open-winding PPMLM and the in-depth analysis of the space voltage vector distribution characteristics of the dual-inverter, a deadbeat two-vector model predictive current control (MPCC) model is proposed in this paper. First, the optimal vector of the inverter 1 is determined by judging the position of the large sector. Second, two optimal vectors of the inverter 2 is determined by judging the position of the small sector. Finally, the duty cycle of the two optimal vectors of the inverter 2 is calculated to realize the proposed deadbeat two-vector MPCC algorithm. Compared with the traditional model predictive torque control (MPTC) and MPCC strategies, the proposed algorithm has the advantages of lower current harmonics (lower 34 % and 44 % under rated conditions, respectively) and better thrust performance (higher 77 % and 61 % under rated conditions, respectively) as well as lower computational complexity. Simulation and experimental results show that the proposed two-vector MPCC has good steady-state and dynamic performances, which can reduce the current harmonics and thrust ripple, and thus improve the motor drive performance compared with the traditional method.

A robust adaptive One Sample Ahead Preview controller for grid-injected currents of a grid-tied power converter with an LCL filter

This paper presents the development of a discrete-time Robust Adaptive One Sample Ahead Preview controller, based on the combination of a Robust Model Reference Adaptive Controller (RMRAC) with the One Sample Ahead Preview controller (OSAP), which is a particular case of the Deadbeat controller. This control structure is applied to grid-side current control of a grid-tied voltage-source inverter (VSI) with an LCL filter. The developed controller is robust enough to be designed considering the LCL filter as a first order model, which is commonly modelled as a third order transfer function, considering the neglected dynamics as unmodelled dynamics on controller design thanks to its adaptive identifier, which is a modified Gradient algorithm. Furthermore, the controller can deal properly with grid impedance uncertainties, which change the resonance peak frequency of the LCL filter, which affects the controller performance and can induce the closed-loop to instability, by incorporation of a majorant signal and the σ-function into the adaptive law, turning it robust. In addition, the predictive nature of the controller, which aims to regulate the current tracking in the minimum time possible (one sample) impacts straightforwardly in the reduction of harmonic distortion on grid-injected currents, improving energy quality, because the transient regime is reduced thanks to the fast dynamics of the adaptive predictive control strategy. To corroborate the controller’s performance and discuss its robustness, Hardware-in-the-Loop and experimental results using a grid-tied 5.5 kW VSI with an LCL filter are presented

A Wide-Range High-Voltage-Gain Bidirectional DC–DC Converter for V2G and G2V Hybrid EV Charger

This article proposes a new wide-range bidirectional dc–dc converter that has an improved voltage gain transfer ratio for use in electric vehicle (EV) applications. The converter preserves the common electrical ground between input and output terminals, and presents a low-voltage stress of switches, high utilization factor, and high efficiency. The proposed EV charger performance is evaluated for a bidirectional power flow in grid-connected vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes. The converter uses a dead-beat current controller in the dc–dc and dc–ac stages, which has a smooth, accurate, and fast response. Finally, experimental results for a 500 W, 40–200 V prototype are provided under a bidirectional power flow in a closed-loop system in the presence of the proposed dead-beat controllers. The obtained results substantiate the theoretical analysis and the applicability of this structure. The converter exhibits the capability for EV battery charging/discharging and demonstrates a peak efficiency of 97.2% and 96.8% in the step-down and step-up modes of operation, respectively.

Luenberger Disturbance Observer-Based Deadbeat Predictive Control for Interleaved Boost Converter

A cascaded deadbeat predictive control strategy with online disturbance compensation is proposed for a three-phase interleaved boost converter in this paper. The topology of the three-phase interleaved converter is symmetric, so the inner loop controller is also designed symmetrically. For the purpose of realizing the error-free tracking of reference value, the deadbeat predictive control method is adopted for inner and outer loops with Luenberger observers, which are designed to estimate and compensate the disturbances of load variation in the power model as well as the unknown resistor of inductance in the current model. To eliminate the influence of a time delay, a two-step predictive control method is adopted in the predictive model. In the aspect of parameter design, the pole placement method is adopted to determine the gain of the observer. A series of simulations and experiments are carried out to test the proposed strategy under steady and dynamic conditions. It is shown that the proposed control strategy has faster dynamic response and stronger robustness against disturbance than the conventional model predictive control.

Deadbeat Predictive Current Control for High-Speed Permanent Magnet Synchronous Machine Drives With Low Switching-To-Fundamental Frequency Ratios

This article analyzes the conventional <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -frame model-based deadbeat predictive current control (DBPCC) methods for high-speed permanent magnet synchronous machine (PMSM) drives with low switching-to-fundamental frequency ratios (SFRs). It shows that the state-of-the-art compensation schemes of control delay and rotor movement effect can improve the control performance but the problem still arises at very high speeds with very low SFRs. Therefore, this article presents a novel DBPCC method for high-speed PMSM drives. The proposed method tracks the machine stator flux vector in the stationary frame to achieve deadbeat control of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis currents. The control delay and rotor movement effect are both precisely considered. Consequently, the control performance and stability of the proposed DBPCC can be guaranteed at high speeds. Extensive simulations and experiments have been performed on a prototype high-speed PMSM drive. The effectiveness of the proposed method and its superiorities against the field-oriented control and the conventional DBPCCs have all been demonstrated.

Robustness of Model-Predictive and Passivity-Based Control in the Three-Phase DC/AC Converter Application

In modern controller design, various solutions for controlling power converter systems can be found depending on their applications, speed of working, pulse width modulation (PWM) techniques, switching frequencies—fc, and different load types. The need to manipulate control parameters can be often observed in classical structures, e.g., well-known PID, repetitive, or deadbeat control particularly sensitive to distinct parameters uncertainties. The purpose of this paper is to present an improved version of controllers designated for a UPS that will be considerably resistant to model changes. Proposed control techniques are independent of unexpected output filter changes: Lf—filter coil inductance and Cf—filter capacitor conductance. The second aspect of this paper is to compare effectiveness of modified predictive MPC (model-predictive control) and feedback PBC (passivity-based control) controllers in reducing output voltage total harmonic distortion (THD) for various load values. The biggest distortions of output voltage were observed during experiments with nonlinear RC load. Both simulation and experimental verification of mismatching parameters were performed and examined. Thanks to the proposed solution, the output voltage THDv quality factor was reduced below 8% in an efficient way for all the applied loads and stayed at the level of 1% when well-matched filter parameters were provided.

Simulation Research on Deadbeat Direct Torque and Flux Control of Permanent Magnet Synchronous Motor

Direct torque control (DTC) is widely used in a permanent-magnet synchronous motor (PMSM), but it has its own shortcomings caused by high torque ripple. Deadbeat-direct torque and flux control (DB-DTFC) is a new torque and flux method compared with DTC. However, the traditional DB-DTFC is often based on rotor-flux-oriented control. The reference voltage of the stator is computed in a rotor-flux-oriented coordinate system, and the solution involves solving quadratic equations, which will increase the burden of computational processing. To improve the computation of the reference voltages and the control performance, this paper proposes a new DB-DTFC algorithm and introduces its basic principles. First, the proposed DB-DTFC algorithm uses the forward Euler equation to solve the reference voltage in a stator-flux-oriented coordinate system. Second, the discrete mathematical model is used to predict the next control current to achieve deadbeat control. Third, the structural model of the proposed DB-DTFC is constructed. Finally, the simulation model of the proposed DB-DTFC algorithm is built with a MATLAB/Simulink platform. The simulation results prove that the proposed DB-DTFC algorithm can achieve better control performance in torque and flux control compared with the DTC algorithm and SVM-based direct torque and flux control (SVM-DTFC) algorithm. In particular, the torque index of DB-DTFC is reduced about 6% in a limited speed range in comparison with the DTC algorithm.

A Deadbeat Current and Flux Vector Control for IPMSM Drive with High Dynamic Performance

In this paper, a new deadbeat stator current and flux linkage vector control (DB-CFVC) scheme for interior permanent magnet synchronous machines (IPMSM) is proposed. The control structure is simplified by implementing the proposed flux linkage vector control method in the α-β stationary coordinate. Unlike conventional deadbeat methods, the dynamic performance of the proposed DB-CFVC can be enhanced while voltage command saturation and over output current are avoided. This is achieved with a “reinforced” phase angle reference of stator flux linkage vector by considering rotor speed error and maximum voltage to properly enhance the quality of the calculated flux phase angle command. By predicting stator flux linkage and current in the stationary coordinate, the deadbeat direct flux linkage vector control based on the one-step delay compensation strategy becomes straightforward and exhibits low sensitivity to motor parameters compared to conventional methods performed in the rotating frame. Then, by developing a practical and robust hybrid flux linkage observer, the proposed DB-CFVC method can work more reliably and effectively than conventional methods. Simulations and experiments are conducted in a drive system for an IPMSM to evaluate the effectiveness and reliability of the proposed method.

Voltage Control of Three-Phase Stand-Alone Photovoltaic System Based on Improved DeadBeat Controller

Stand-Alone Photovoltaic systems (SAP) based on power electronics converters have found high attention, recently. According to the rate of power, three phase inverter is more applicable for high power applications. However, unbalanced loading condition is inevitable condition for these inverters. To prepare a current flow for inevitable fourth wire current, 4-Leg inverter is a beneficial solution. To sinusoidal load voltage shaping, the control method is very important since it must maintain three-phase balanced sinusoidal load voltages. Among different linear and non-linear control methods, deadbeat (DB) method offers high simplicity as well as good accordance for digital implementation. But, it suffers from two sampling period delay which deteriorate the load voltages quality and sometimes, results in instability of the control system. In this paper, new DB control method with delay compensation strategy is proposed which not only have the usual benefits of the DB control method but also, it overcomes the aforementioned weakness. Finally, a 3kW laboratory test bench based on DSP-Based digital control board is provided to consider the result of the proposed control methods. Several tests under various inverter loads such as no load, full linear load and 100% unbalanced load are done to evaluate the benefits of the proposed system.

Voltage-Sourced Converter Fed High-Speed Switched Reluctance Motor Drive System With Energy Feedback and Near-Unity Power Factor

The diode bridge rectifier fed asymmetric half-bridge converter (AHBC) is conventionally employed to drive switched reluctance motors (SRMs), which leads to poor grid-side power quality. In the proposed system, a topology made up of a voltage-sourced converter and an AHBC is employed to drive the high-speed SRM. Stable SRM operation can be obtained by manipulating the active power flowing to motor side, and on the basis of that, the grid-side power quality is enhanced by directly manipulating input reactive power. Predictive deadbeat control with disturbance observer is employed to follow the power references, thereby achieving controllable speed, energy feedback, near-unity grid-side power factor, and low grid-side current distortion simultaneously. Additionally, an improved asymmetric modulation method is developed for switching frequency reduction. Experiments are carried out to test the proposed drive system in steady and dynamic conditions. Performance comparisons validate the improvement of the proposed high-speed SRM drive system.

Model-Free Predictive Current Control of a PWM Rectifier Based on Space Vector Modulation Under Unbalanced and Distorted Grid Conditions

Among various control strategies for pulsewidth-modulated (PWM) rectifiers, model-based predictive current control (MBPCC) based on space vector modulation (SVM) is a simple and effective method due to its quick dynamic response and good steady-state performance. However, SVM-based MBPCC (SVM-MBPCC) suffers from parameter variations and grid disturbances, which are common in practical applications due to temperature effects, saturation, grid faults, and so on. Recently, model-free predictive current control (MFPCC) based on current differences has been proposed to address the problem of parameter robustness. However, this approach suffers from stagnant updating of the current differences, and the steady-state ripples are still high due to the application of a single vector in one control period. This article proposes an SVM-MFPCC, which combines the merits of both SVM-MBPCC and MFPCC. The proposed method uses an ultralocal model rather than a conventional accurate model of the PWM rectifier, which is updated online based on the voltages and currents in past control periods. By using this ultralocal model, a voltage reference to nullify the current error can be calculated based on the principle of deadbeat control and is subsequently synthesized via SVM. Furthermore, by adding an appropriate compensation power to the original power references, the proposed method can achieve sinusoidal and balanced grid currents even under unbalanced and distorted grid conditions. The proposed method is compared to conventional SVM-MBPCC under various grid conditions, and the results of simulations and experiments confirm its effectiveness.

A Novel Online Parameter Identification Algorithm Designed for Deadbeat Current Control of the Permanent-Magnet Synchronous Motor

The deadbeat control is one of the widely concerned control methods for the permanent-magnet synchronous motor (PMSM) due to its fast dynamic performance. However, its control performance relies heavily on the accuracy of the PMSM model parameters, which may vary with the operation cases. In this article, a novel online parameter identification algorithm is proposed for the PMSM deadbeat control. First, an identification model is established to estimate the parameter errors from the offsets of the deadbeat control, in which the nonlinearity of the voltage source inverter is fully concerned. Then, a novel “parameter perturbation method” is proposed for gathering the essential data to solve the rank deficient problem in the parameter identification process. It does not need to inject additional instructions in the control, resulting in no impact on the normal operation of the PMSM. The Adaline neural network is employed to achieve the online acquisition of parameter identification results. Finally, the effectiveness and superiority of the proposed algorithm are verified by experimental results on a PMSM platform.

Enhanced Predictive Model Based Deadbeat Control for PMSM Drives Using Exponential Extended State Observer

In order to improve robustness and dynamic tracking performance, this article proposes a deadbeat control method based on an enhanced predictive model and an exponential extended state observer (EDB-EESO). By incorporating parameter mismatches and load perturbation as lumped disturbance, extended state-space realizations of permanent magnet synchronous motor (PMSM) speed and stator current mathematical model are presented. To achieve higher robustness under the disturbance, the exponential extended state observer (EESO) is proposed based on the extended state-space realizations. Combining the EESO, the enhanced predictive model is designed to improve overshoot and settling time caused by the system inertial link. To eliminate the effect of time delay, a two-step predictive control method is adopted in the enhanced predictive model. Furthermore, the cost function of EDB-EESO is evaluated by utilizing the deadbeat control method and the stability of EDB-EESO is proved. The experimental results validate the strong robustness and excellent dynamic tracking performance of EDB-EESO in PMSM drives compared with conventional methods.

Robust Predictive Rotor Current Control of a Doubly Fed Induction Generator Under an Unbalanced and Distorted Grid

Under unbalanced and distorted grid conditions, the performance of conventional control methods for doubly fed induction generators (DFIGs) severely deteriorates, resulting in highly distorted stator and rotor currents. Furthermore, the performance can further degrade when the machine parameters used in such a controller differ from their actual values due to temperature, saturation and so on. To solve these problems, this paper proposes a robust predictive rotor current control (R-PRCC) scheme for a DFIG with multiple aims, even under unbalanced and distorted grid conditions. First, the reference value of the positive-sequence component of the rotor current is obtained from the outer power loop with the help of cascaded delayed signal cancellation (CDSC), which ensures the control aim of sinusoidal and balanced rotors currents. By investigating the relationship between stator currents and rotor currents, a new rotor current reference without using DFIG parameters can be obtained to satisfy multiple control aims, including sinusoidal and balanced stator currents, constant output active power and constant electromagnetic torque. Second, by introducing an extended state observer (ESO), the total disturbance caused by model uncertainty can be quickly estimated, and deadbeat control is further incorporated to achieve fast and accurate control of the rotor current. The proposed R-PRCC scheme is compared to conventional field-oriented control (FOC) and model predictive rotor current control (MPRCC). Simulated and experimental results are obtained for a 1.5-kW laboratory. The DFIG system confirms the effectiveness of the proposed method.

Novel deadbeat predictive control strategy for DFIG’s back to back power converter

To successfully carry out a wind energy conversion system, it is necessary to simultaneously control the rotor and the grid side. This paper proposes a doubly-fed induction generator's predictive power control. While the powers are controlled indirectly through currents, the latter is controlled using the deadbeat command. Based on discrete-time, the control suggests at each sample period the required voltages to the the-back-to-back converter to reach the desired setpoints, control the powers, and the DC link voltages. For these reasons, a presentation of the system is given first, then a description of the predictive control, followed by applying this strategy on the rotor side control and grid side control. Finally, a random wind profile was applied to analyze the system's performance with a unitary power factor. The simulation results are presented in the MATLAB/Simulink environment using a 1.5 kW DFIG. The results obtained by applying a random wind profile have well fulfilled the objectives of the control and the system robustness is approved by the excellent tracking allowing the machine's internal parameters variation. By comparing the quality and the tracking reference of the proposed control method to other control methods, the deadbeat controller was very promising.