Deadbeat Control Research Articles

Deadbeat Current Controller for Bidirectional Dual-Active-Bridge Converter Using an Enhanced SPS Modulation Method

This letter proposes a deadbeat current controller for isolated bidirectional dual-active-bridge DC-DC converter. The controller uses an enhanced single phase shift modulation method by exploiting pulse width as an extra control variable besides phase shift ratio, the only control variable of the conventional single phase shift modulation. The current reference can be tracked within one switching cycle during the bidirectional power transmission and transition of the two directions. Deadtime effect is studied and the compensation method for the controller is proposed. Parameter robustness is analyzed by mathematical derivation and the online autotuning method for the inductance is presented. The proposed deadbeat current controller is simple and easy for implementation. Moreover, it shows superior dynamic performance, which is verified by experimental results during the transient processes of the converter. The effectiveness of the autotuning method is also validated by the prototype experiment.

Model-Free Predictive Current Control of a DFIG Using an Ultra-Local Model for Grid Synchronization and Power Regulation

Traditional model predictive control has difficulty in achieving satisfactory control performance when parameter identification is inaccurate or when a parameter changes. To solve this problem, this article proposed a new model-free predictive current control (MFPCC) scheme for a doubly fed induction generator (DFIG), which combines an ultra-local model with predictive current control (PCC). This method replaces the mathematical model of a DFIG with an ultra-local model and has strong parameter robustness. In addition, this method is suitable for the synchronization and power regulation processes of a DFIG, and it is also easy to apply to a DFIG with uncertain parameters. The proposed method is compared to traditional model-based deadbeat control with space vector modulation (SVM), and the presented experimental results confirm its superiority and effectiveness.

Deadbeat predictive direct power control of interleaved buck converter-based fast battery chargers for electric vehicles

This paper presents a deadbeat predictive direct power control (DB-DPC) scheme for a fast battery charger to improve its dynamic performance and stability. Recently, battery chargers have been adopting paralleled multi-leg converters based on silicon carbide (SiC) devices to increase power capacity, which reduces the charging duration. However, the inherent instability of the battery is regarded as a crucial issue during the fast charging process. Therefore, the proposed DB-DPC provides a stable steady state since it includes real-time estimation of the variable battery impedance. Furthermore, the DB-DPC effectively minimizes the rising and settling time, which demonstrates fast-dynamic response characteristics when compared to proportional–integral (PI) control. The control performance is verified by various simulation and experimental results.

Approach for classifying continuous control set‐predictive controllers applied in AC motor drives

In this article, basic concepts, operating principles and important characteristics of continuous control set-predictive controllers (CCS-PCs) applied to AC motors are explained in detail. Based on the existence or absence of cost function as well as the method used to find the optimal control action, CCS-PCs can be categorised into the following three categories: predictive controllers without cost function, predictive controllers with a cost function (or model predictive controllers) and deadbeat controllers. To identify the advantages and disadvantages of each category, one of the recent algorithms of each category is selected and implemented experimentally. Then, various experimental tests are conducted where performances of all the algorithms are assessed in a comprehensive manner by evaluating stator-flux ripple, torque ripple, stator current harmonics, robustness against parameter changes, computational complexity, memory requirement and torque dynamic response. To achieve general and meaningful conclusions, the analysis is performed on a traditional three-phase two-level voltage source inverter used to control an interior permanent-magnet synchronous motor. Based on the theoretical discussions and experimental results, it is indicated that which category of CCS-PCs can be adopted in high performance AC motor drives.

An Extendable Quadratic Bidirectional DC–DC Converter for V2G and G2V Applications

In this article, we propose an extendable quadratic bidirectional dc-dc converter that has an improved voltage transfer ratio (VTR) with the capability of redundancy and modularity for electric vehicle applications. As n modules are embedded, its VTR becomes n times higher for both directions of currents. Furthermore, the common electrical ground between the input and output is preserved. This is a simple structure with the lowest rating of semiconductors in the family of quadratic bidirectional converters leading to ease of control ability. The proposed converter performance is evaluated in both power flow direction using the deadbeat controller, which is a smooth, accurate, and fast response. Finally, the process of charging/discharging of a lithium-ion battery is controlled through the proposed converter. 500-W experimental results are provided in both power flow directions in a closed-loop system in the presence of the proposed controller. The obtained results verify the applicability of this structure.

Design of an active front-end rectifier controller with an accurate estimation for the dynamic of its deadbeat current control loop

This paper proposes a control strategy for a grid-connected single-phase Active Front-End (AFE) rectifier that deals with both of ac-side sinusoidal current quality during steady state and dc-bus voltage fluctuations under transient operation issues. This control strategy consists of two control loops. The outer one is used for the control of the dc-bus voltage and is based on a PI controller. The inner loop is used for the control of the grid current and is based on a Deadbeat Predictive (DP) controller that operates with a fixed switching frequency. In order to prevent interactions between the two control loops, the outer control loop dynamic should be at least ten times lower than that of the inner control loop dynamic. For this purpose, a theoretical approach for computing the dynamic of the deadbeat predictive current control is described. Then, the dc-bus voltage controller is designed so that the following constraints are satisfied: (a) the bandwidth of the voltage control loop must be very low with regard to that of the current control loop to prevent interaction between them; (b) the third harmonic component of the grid current resulting from the double line frequency ripples of the measured dc-bus voltage has to be mitigated complying with standards, and (c) reducing the transient fluctuations of the dc-bus voltage caused by instantaneous and high level changes of the active power consumed by the dc load. Simulation and experimental results for the control algorithm validation are also presented and discussed.

Improved Model Predictive Current Control of Single-Phase Five-Level PWM Rectifier

In this paper, a single-phase five-level rectifier with coupled inductors is studied. First, a discrete mathematical model of a single-phase five-level rectifier is created in two-phase(αβ). A traditional single vector finite control set model predictive control (FCS-MPC) algorithm is improved to overcome the problems of a varying switching frequency, the large amount of time needed for calculation, and the inaccurate setpoint of current loop tracking. Then, the objective function of the system is established, and a simple objective function is used instead of an iterative optimization of the traditional FCS-MPC algorithm. At the same time, to eliminate the delay error and to reduce harmonic distortion, deadbeat control technology is introduced. Finally, the simulation and experimental results show that the improved model predictive current control algorithm not only retains the fast response of traditional model predictive control, but also has the advantages of fixed switching frequency, small calculation time, and small current steady-state error.

High Buck in Buck and High Boost in Boost Dual-Mode Inverter (Hb2DMI)

The application of the dual-mode time-sharing technique in novel transformerless photovoltaic (PV) inverters is proposed and investigated. The simultaneous high step-down or high step-up conversion with 97.6% peak efficiency and injected current with total harmonic distortion <; 2% are achieved. The leakage current problem, which is a main concern with the transformerless PV inverters, is around 20 mA. The indirect current control, especially at transition of modes of operation is highly improved by utilizing a fast dead-beat control scheme. The working principles of the proposed converter show that the step-down and the step-up voltage gains are (D/(1-D)) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and D/(1-D) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , respectively. Furthermore, a 1 kW, 220 VAC and 200 VDC experimental prototype is implemented to confirm the theoretical achievements.

Active Demagnetization Fault Compensation for Axial Flux Permanent-Magnet Synchronous Machines Using an Analytical Inverse Model

In this article, a fault tolerant deadbeat controller is proposed, which is able to compensate for both partial and uniform demagnetization faults in axial flux permanent-magnet synchronous machines with double rotor, even with asymmetric defects in both rotors. For this purpose, the system model used by the deadbeat controller is equipped with a look-up table of the back-emf, in function of the mechanical rotor position. This look-up table is generated by means of an analytical model based on the magnetic vector potential. With this information, the deadbeat controller can eliminate both the additional bias and ripple in the stator current components caused by demagnetization faults. The proposed control strategy is validated on a 4 kW test set-up of an axial flux permanent-magnet synchronous machine with yokeless and segmented armature topology fed by a three-phase two-level voltage source inverter, both by simulations and experiments. Key performance indicators concerning bias and ripple of the current components illustrate the superior performance of the proposed control strategy in comparison to a standard deadbeat controller without an up-to-date look-up table of the back-emf.

Two-Stage Model Predictive Control of Neutral-Point-Clamped Inverter-Fed Permanent-Magnet Synchronous Motor Drives Under Balanced and Unbalanced DC Links

Controlling a three-level neutral-point-clamped (3L-NPC) inverter-fed permanent-magnet synchro-nous machine (PMSM) drive is a challenging task, especially when the dc-link voltage is unbalanced. The unbalanced dc-link voltages, which are with some of the voltage vectors varying in magnitude and phase, lead to highly distorted stator current. In this article, a two-stage model predictive control (MPC) is proposed for the 3L-NPC inverter-fed PMSM drive. In the proposed MPC method, control of the 3L-NPC inverter is decoupled into two stages. In the first stage, three switching states are determined by small hexagon selection using finite control set MPC. The rest switching states are controlled using the multiple vector MPC in the second stage. In the two-stage MPC, the number of switching state evaluations can be significantly reduced, and the nonlinearity caused by the unbalanced dc links can be included in the duty cycle optimization process, leading to improved output current quality under unbalanced dc links and reduced computational burden. Moreover, the output switching frequency is fixed due to the employment of the multiple vector MPC. A thorough experimental evaluation of the proposed MPC method with the deadbeat control with the pulsewidth modulation strategy has been conducted to validate the superiority of the proposed method.

Deadbeat Predictive Power Control with Fuzzy PI Compound Controller and Power Predictive Corrector for PWM Rectifier Under Unbalanced Grid Conditions

Under unbalanced grid conditions, the DC side voltage of pulse width modulation (PWM) rectifier will overshoot during start-up and reference voltage transients, which may lead to system instability. In this paper, a deadbeat predictive power control (DPPC) with fuzzy PI compound controller (FPCC) and power predictive corrector (PPC) is proposed to solve that problem. Firstly, the parameters of the PI controller are adjusted online by the fuzzy control rule of the FPCC to eliminate the overshoot of the DC side voltage and contribute to faster dynamic responses, which thereby could correct the reference active power. Secondly, the static error between the reference and system active powers is reduced by accumulative predictive errors in the PPC. The simulation is carried out under ideal and unbalanced grid conditions. The result shows that the proposed control scheme can effectively eliminate the overshoot of DC voltage, reduce the static error of active power, and improve the dynamic response and anti-interference ability of the rectifier.

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed.

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

Circulating Harmonic Currents Suppression of Level-Increased NLM Based Modular Multilevel Converter With Deadbeat Control

This article first analyzes the effect of the level-increased nearest level modulation (NLM) to the circulating current of the modular multilevel converter (MMC). The total inserted submodule (SM) number in one phase-leg of the MMC is variable using the level-increased NLM, which can significantly increase the peak-to-peak value of the circulating harmonic currents. Then, a circulating harmonic currents suppression method is proposed by applying deadbeat control for the MMC with level-increased NLM. Compared with the existing direct circulating current control approaches for the MMC, the proposed method presents specific extension and adjustment principle of the total inserted SM number. Therefore, the proposed method can improve the dynamic control performance and handle large circulating harmonic currents at steady state. And it can well coordinate the modulation and circulating harmonic currents suppression stages to avoid disturbing the ac-side output voltage while regulating the circulating current. The effectiveness of the proposed method is evaluated by a single-phase industrial-level simulated MMC system and a laboratory experimental platform.

Predictive deviation filter for deadbeat control

Deadbeat control calculates excitation by a differential equation model that takes measurements of state variables as initial values and instructions as terminal values. Ideally, this excitation can force state variables to track instructions in the succeeding control interval. However, in a practical system, noises in measured signals can mislead the control system and degrade its performance with increased ripples and harmonics. Therefore, some filters are often used in measurements, but their inherent delay can lead to inaccurate initial values and cause severe overshoots in dynamic cases. In this study, a new type filtering algorithm called predictive deviation filter is proposed for deadbeat control, which filters only the predicted deviation obtained by removing the expected values from measured ones, and then the real values of state variables are recovered. With this method, the influence of the filter delay can be limited only on the deviation which is a small part of the signal, significantly improving the accuracy of the initial values. Furthermore, a comprehensive frequency-domain analysis of the predictive deviation filter is provided. Finally, the new filtering algorithm is applied to drive control of permanent magnet synchronous motor. The simulation and experimental results verify the effectiveness and performance of this approach.

Linear Feedback Dead-Beat Control for Modular Multilevel Converters: Validation Under Faults Grid Operation Mode

The cascaded control approach is widely used to control the modular multilevel converter (MMC). Such approach allows to manage all MMC state variables in a decoupling manner based on modes separation. This separation introduces conditions related to control objectives response time resulting in slow dynamics. This will limit the use of the potential of MMC energy that is considered as a freedom for ac and dc grids ancillary services. On another side, robustness properties for a given control are also of a great interest when considering unmodeled uncertainties and disturbances. Starting from these requirements, a linear feedback dead-beat control is proposed in this article to accelerate the inner loops and consequently the outer ones (control objectives). The proposed control, based on exact discrete-time model of the MMC in which the sampling period is considered a priory in the control design, is synthetized by taking into account the control outputs saturation. The stability proof of the control and the robustness analysis as well as experimental results under fault grid operations highlighted on small-scale MMC will be presented in this article. The comparison with a continuous-time sliding mode control shows the advantage of the proposed control regarding the response time and undesired oscillation reduction.

Implementation of dead beat controller using Particle Swarm Optimization for software defined network

Renewable energy sources is largely adopted for generation of electrical energy and various methodologies have been proposed in this area This paper focuses on analysis, design and implementation of DC/DC buck–boost converter towards producing the hybrid prototype, consisting of 3kW PV and 3.2 kW PMSG using wind energy conversion system. Particle Swarm Optimization algorithm is employed for regulation of the output voltage generated. To extract maximum power, PSO algorithm is adopted for hybrid renewable energy sources which are considered as NP hard problem. To eliminate the harmonics and to have maximum electrical power delivered to the grid on polynomial time, the single phase or three phase sinusoidal pulse width modulation (SPWM) inverter has been employed with PQ control strategy using metaheuristic based approximation. The proposed PSO technique produces a steady state DC link voltage of 400 V with reduced harmonic distortion using LC filter. Further, the application of capacitor bank arrangement reduces the ripples present in the output voltage variations. The simulation outcomes prove the efficiency of the proposed model along its measurements.

Deadbeat Predictive Current Control for Circulating Currents Reduction in a Modular Multilevel Converter Based Rail Power Conditioner

This paper presents a deadbeat predictive current control methodology to reduce the circulating currents in a modular multilevel converter (MMC) when it operates as a rail power conditioner (RPC) in a conventional railway system-based V/V connection. For this purpose, a half-bridge MMC based on half-bridge submodules, operating as an RPC is explained, and the total system is denominated as a simplified rail power conditioner (SRPC). The SRPC in this study is used to compensate harmonics, reactive power, and the negative sequence component of currents. This paper explains the SRPC system architecture, the key control algorithms, and the deadbeat predictive current control methodology. Mathematical analysis, based on the MMC equivalent circuit, is described and the reference equations are presented. Moreover, simulation results of the deadbeat predictive current control methodology are compared with the results of the conventional proportional-integral (PI) controller. This comparison is to verify the effectiveness of the proposed control strategy. Simulation results of the SRPC show reduced circulating currents in the MMC phases when using the predictive control approach, besides accomplishing power quality improvement at the three-phase power grid side.

Sagittal SLIP-anchored task space control for a monopode robot traversing irregular terrain

As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane, the spring-loaded inverted pendulum (SLIP) model has been extensively employed in both biomechanical study and robotics research. Aiming at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass (CoM) with maneuverability, this study presents a novel two-layered sagittal SLIP-anchored (SSA) task space control for a monopode robot to deal with terrain irregularity. This work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy, and a two-layered SSA task space controller is subsequently developed for the monopode robot. The higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller, which generates an adaptive reference trajectory for the CoM. The lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode robot. Consequently, an adaptive hopping behavior is exhibited by the robot when traversing irregular terrain. Simulation results have demonstrated the effectiveness of the proposed method.

Accurate Discrete-Time Modeling for Improved Torque Control Accuracy for Induction Machine Drives at Very Low Sampling-to-Fundamental Frequency Ratios

Operations at low sampling-to-fundamental frequency (S2F) ratios of induction machines are required for high-power or high-speed applications. The traditional indirect field-oriented control is open-loop control on torque, which is sensitive to machine parameters and degrades at low S2F ratios. Deadbeat-direct torque and flux control (DB-DTFC) is closed-loop control on torque but also degrades at low S2F ratios with inaccurate discrete-time approximations. This article presents a methodology of accurate discrete-time modeling for the flux and current observer and the deadbeat controller used in DB-DTFC. The current, flux, and torque estimations are improved with the proposed observer model at very low S2F ratios. The torque control is enhanced and insensitive to machine parameters under high-speed low-S2F-ratio conditions. The increased computational time of the proposed model is insignificant for real-time implementations.

Hybrid Control Strategy of MPC and DBC to Achieve a Fixed Frequency and Superior Robustness

In this paper, a hybrid control strategy for power converters, based on improved deadbeat control (DBC) and improved finite control set model predictive control (MPC), is proposed. The presented control strategy employs a switched method to achieve a fixed switching frequency while maintaining a fast transient time. Moreover, the proposal incorporates error correction to achieve superior robustness. A prototype of a single-phase voltage source rectifier is established to verify the performance of the proposal. The comparative results with conventional MPC are given and illustrate the merits of the proposed control method.