Search Results (47)

The traditional deadbeat predictive current control (DPCC) strategies for a permanent magnet synchronous motor (PMSM), such as those based on an extended state observer (ESO) and quasi-resonant extended state observer (QRESO), usually require large observer bandwidth, rendering the system sensitive to noise. To address this issue, this paper proposes a cascaded quasi-resonant extended state observer-based DPCC (CQRESO-based DPCC) strategy. Specifically, the CQRESO is utilized to estimate the predicted values of d-axis and q-axis currents, as well as the system total disturbance caused by the deterministic and uncertain factors at time instant k + 1. Subsequently, the required control command voltage at time instant k + 1 is then calculated according to the deadbeat control principle. Finally, the comparative simulation results with ESO-based DPCC and QRESO-based DPCC strategies demonstrate that the proposed strategy can achieve dynamic and robust performance comparable to the ESO-based and QRESO-based DPCC strategies while utilizing a smaller observer bandwidth. Additionally, it exhibits superior steady-state performance and 5th and 7th harmonic current suppression capabilities (in the abc reference frame). Full article

Digital control in UPS systems is currently the only reasonable way of controlling a voltage source inverter (VSI). The control frequency range is restricted to up to about 1 kHz owing to the output low-pass LC filter, which should also maintain the output voltage during one switching period for the step unload. The measurement channels in the low-pass frequency range can be modeled as delays equal to some switching periods. A reasonably high (about 50 kHz) switching frequency minimizes the delays of the measurement channels. Two control systems will be compared—the pure discrete control, in this case a one-sample-ahead preview deadbeat control (OSAP), and a discretized passivity-based control (PBC). The OSAP control is easy to realize, is very fast, and enables one to obtain a steady state in a restricted number of steps after disturbance. However, the single-input single-output deadbeat control version is useless because it depends very strongly on the parameters of the inverter. The multi-input single-output OSAP (MISO-OSAP) control is directly based on discrete state equations (we treat the output voltage, output current, and inductor current as the measured state variables) and works perfectly for the nonlinear rectifier RC load (PF = 0.7) in a system without delay. The version of this with a linear prediction of state variables by means of a full-order state Luenberger observer (MISO-OSAP-LO) will be used in systems with different delays and compared with the discretized MISO passivity-based control without prediction for relatively high switching frequency (about 50 kHz). The aim and the novelty of the paper are in enabling a choice between one of these control systems for high switching frequency VSI with delays in the measurement channels. Full article

To suppress current and torque ripples, this paper proposes a novel deadbeat predictive current control strategy based on an adaptive sliding mode observer for permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) drives. The parameter sensitivity of predictive current control is analyzed, and a sliding mode observer is employed to calculate the parameter disturbances for voltage compensation. The predicted current is utilized instead of the sampled current to address the one-step delay issue, effectively suppressing the adverse effects of parameter mismatch in predictive control. The adaptive control parameter module suppresses the chattering phenomenon in sliding mode control and enhances the observer’s adaptability under varying load conditions. The effectiveness of the proposed strategy is validated on a 2.2 kW PMa-SynRM platform. This strategy can suppress current and torque fluctuations under complex operating conditions, which has significant implications for electric vehicle drive control. Full article

In modern marine vessels equipped with electric propulsion systems, rectifiers are commonly used as part of the setup. However, the conventional deadbeat predictive direct power control strategy for three-phase voltage source pulse-width modulation (PWM) rectifiers tends to underperform when subjected to load variations and external disturbances. To address these limitations, this paper proposes an enhanced linear active disturbance rejection control (LADRC), incorporating virtual capacitance and an improved equivalent input disturbance strategy. The integration of virtual capacitance in the LADRC is specifically applied during load transitions. Virtual capacitance is a capacitor element simulated through the control strategy. It enhances voltage stability and dynamic response capability by compensating for voltage fluctuations and power deficits in the system. By providing a virtual active power, this approach substantially improves power tracking performance, reducing the DC voltage drop and settling time by 60% and 74%, respectively. In addition, the proposed strategy is easy to implement and does not add complexity to the LADRC. Moreover, the equivalent input disturbance is refined through virtual capacitance, enabling accurate disturbance estimation. As a result, the active power ripple and current total harmonic distortion under disturbances are reduced by 44% and 40%, respectively. The stability of the proposed strategy is comprehensively analyzed, and experimental results from a prototype system validate its effectiveness and accuracy. Full article

Aiming at the issues of control delay and circuit parameter mismatch in three-phase modular multilevel converters (MMCs), this paper proposes a model assisted extended state observer-based deadbeat predictive current control (MAESO-based DPCC) strategy to regulate the AC-side current and internal circulating current. The model assisted ESO (MAESO) is employed to estimate the predicted values of the d- and q-axis components of the AC-side current, the internal circulating current, and system disturbance caused by the other certain and uncertain factors (including circuit parameter changes) of MMC at the time instant k + 1, and the required control input at the time instant k + 1 is then calculated based on the deadbeat control principle. The proposed control strategy not only maintains excellent steady-state performance and fast dynamic response characteristics similar to those of the traditional deadbeat predictive current control (DPCC) strategy but also has stronger robustness in the case of circuit parameter changes. The proposed control strategy was ultimately compared with the traditional DPCC strategy via experiments, and the experimental results verify the feasibility and effectiveness of the proposed control strategy. Full article

Permanent magnet linear synchronous motors (PMLSMs) with stator segmented structures are widely used in the design of high-power propulsion systems. However, due to the inherent delay and segmented structure of the systems, there are parameter disturbances in the inductance and flux linkage of the motors. This makes the deadbeat predictive current control (DPCC) algorithm for a current loop less robust in the control system, leading to a decrease in control performance. Compensation methods such as compensation by observer and online estimation of parameters, are problematic to apply in practice due to the difficulty of parameter adjustment and the high complexity of the algorithm. In this paper, a robustness-improved incremental DPCC (RII-DPCC) method—which uses incremental DPCC (I-DPCC) to eliminate flux linkage parameters—is proposed. The stability of the current loop was evaluated through zero-pole analysis of the discrete transfer function. Current feedforward was introduced to improve the stability of I-DPCC. The inductance stability range of I-DPCC was increased from 0.8–1.25 times to 0–2 times the actual value, and the theoretical stability range was increased more than 4 times, effectively improving the robustness of the predictive model to flux linkage and inductance parameters. Finally, the effectiveness of the proposed method was verified through numerical simulation and experiment. Full article

In this paper, a sample voltage dead-beat control based on differentiative voltage prediction (DVP) and switching-cycle extension (SCE) is presented to achieve optimal transient response for DC-DC converters under discontinuous conduction mode (DCM) operation. Firstly, to improve load transient response, a DVP method is proposed to estimate the load. With the estimated load, the controller realizes load current feedforward and thus improves the transient response with a wide load range. Secondly, an SCE strategy is proposed to enlarge the output current range and output voltage slew rate, both of which have limited value under conventional digital pulse width modulation (DPWM). When the output current reaches the limited value, the proposed strategy increases the switching cycle to enlarge the current range without losing DCM operation. Finally, combining DVP with SCE, the converter not only achieves optimal response in large signal transients, but also doubles the load range in DCM operation. Full article

This article proposes an improved model-free deadbeat predictive current control (MFCC) method for permanent magnet synchronous motors (PMSMs) based on the ultralocal model and H∞ norm. Firstly, the traditional deadbeat predictive current control (DPCC) method is introduced and a theoretical analysis is conducted on its sensitivity to parameters. Building upon this, the limitations of model dependence and the limited robustness of the deadbeat predictive current control method based on the extended state observer (ESO-DPCC) are theoretically analyzed. Furthermore, an improved MFCC method based on the ultralocal model is proposed, and the influence of the observer on MFCC is theoretically analyzed. This study combined the proposed method with the H∞ norm, and the optimal coefficients of the observer were tuned to enhance the robustness and dynamic performance of the current loop. Finally, the proposed algorithms were validated on a 400 W PMSM platform. Full article

To address problems that traditional two-stage inverters suffer such as high cost, low efficiency, and complex control, this study adopts a quasi-Z-source cascaded multilevel inverter. Firstly, the quasi-Z-source inverter utilizes a unique impedance network to achieve single-stage boost and inversion without requiring a dead zone setting. Additionally, its cascaded multilevel structure enables independent control of each power unit structure without capacitor voltage sharing problems. Secondly, this study proposes a current-predictive control strategy to reduce current harmonics on the grid side. Moreover, the feedback model of current and system state is established, and the fast control of grid-connected current is realized with the deadbeat control weighted by the predicted current deviation. And a grid-side inductance parameter identification is added to improve control accuracy. Also, an improved multi-carrier phase-shifted sinusoidal PWM method is adopted to address the issue of switching frequency doubling, which is caused by the shoot-through zero vector in quasi-Z-source inverters. Finally, the problems of switching frequency doubling and high harmonics on the grid side are solved by the improved deadbeat control strategy with an improved MPSPWM method. And a seven-level simulation model is built in MATLAB (2022b) to verify the correctness and superiority of the above theory. Full article

This article proposes a new deadbeat predictive current control (DPCC) method based on a sliding-mode observer (SMO), which is applied in the field of permanent magnet motor control. A novel DPCC control method based on SMO is proposed according to the inherent issues of DPCC, which can effectively suppress internal parameter mismatch disturbances and external disturbances in the current loop. The mathematical model and derivation process of the proposed method are introduced. A simulation model is built and the effectiveness of the proposed method is verified. An experimental platform is built and the superiority of the proposed method is verified based on comparative experiments. Experimental results show that the proposed algorithm has strong robustness to the motor parameter mismatch. Compared with extended state observer (ESO) and adaptive observer (AO), the proposed algorithm has faster response speed and higher steady-state accuracy. Full article

Compared to the conventional finite control set model predictive control (FCS-MPC), the double vector model predictive current control (DVMPCC) for permanent magnet synchronous motors (PMSMs) has a better steady-state performance without significantly increasing the switching frequency. However, determining optimal vectors with their dwell times requires a high computational burden. A low-complexity DVMPCC in the steady state was proposed in this study to address this problem. Firstly, the operating state of the motor was judged according to the speed error. During steady-state operation, the first optimal active vector was selected from three candidate vectors adjacent or identical to the active vector applied in the previous control period, reducing the number of comparisons by half. Next, the second optimal vector was selected from the other two active vectors, and the zero vector, the second optimal vector with the duty cycle, was determined according to the deadbeat condition of the q-axis current and cost function minimization. Finally, simulation and experimental results proved that the proposed low-complexity DVMPCC for surface-mounted permanent magnet synchronous motors is practical and feasible. Full article

The conventional finite control set model predictive current control (FCS-MPCC) suffers from suboptimal steady-state performance, primarily due to the limited selection of only eight basic voltage vectors in each control cycle. To overcome this limitation, the proposed extended control set MPCC (ECS-MPCC) utilizes an control set consisting of 818 selectable vectors, enabling a more refined voltage output and achieving a deadbeat response for current control by minimizing the cost function. To mitigate the computational burden resulting from the substantial increase in voltage vectors, a simplified search strategy is devised, which can be extended to other multi-objective cost functions. Remarkably, based on the inherent parallelism of the algorithm, the ECS-MPCC is implemented on an FPGA, further reducing the overall control time of the current loop to an impressive 0.61 μs. Through simulation and experimental tests on a laboratory PMSM driver, the effectiveness of the proposed ECS-MPCC strategy is validated. The experimental results demonstrate a significant reduction of 79% in the total harmonic distortion of phase currents compared to the conventional FCS-MPCC approach. This improvement underscores the superiority of the ECS-MPCC in enhancing the performance of PMSM drives, thereby illustrating its potential for practical implementation in real-world applications. Full article

Deadbeat predictive current control (DPCC) has excellent dynamics and can achieve current control with less computational effort. However, its control performance relies on the precision of the parameters of the motor. Current static error will be generated and control performance will be decreased when the predictive model parameters do not correspond to the practical parameters of the motor. In this article, a weakened integral sliding mode compensation method is proposed which converts the current error into a voltage compensation term and adds it to the prediction control output to effectively compensate for the steady-state error. In addition, a boundary layer is introduced to weaken the integral so as to solve the problems of integral saturation and overshoot caused by the introduction of the integral term when the error is large. Moreover, weight factors are introduced to optimize the feedback current, which enhances the robustness of the system. In the end, the effectiveness of this method is verified via simulation and experimental results. Full article

In the field-weakening region, the traditional field-weakening method for induction motor drives based on model predictive control (MPC) is to take a no-load operation as the premise and adjust the flux reference in the cost function proportional to the inverse of the rotor speed, which leads to poor torque output. This paper presents a novel field-weakening method for IM drives based on MPC. Considering the induction motor field-weakening limiting conditions and according to the speed adaptive field-weakening strategy with a voltage closed-loop, the speed adaptive field-weakening controllers were designed to optimize the references of the excitation current and torque current. In the rotor field-orientation d–q coordinate system, the stator flux amplitude and torque reference values were optimized by the optimal distribution current. Then, according to the dead-beat control principle, they were converted into an equivalent stator flux vector reference. Moreover, the stator voltage vector reference can be obtained. For an induction motor fed by a three-level neutral point clamped (3L-NPC) inverter, the cost function was constructed by combining all the constraints, including the voltage vector, the neutral potential balance, and the switching frequency. In this way, the high-performance field-weakening operation for the induction motor based on a model predictive control can be realized. The simulation and experiment results show that the proposed method can increase the torque output by 22% in the field-weakening region; at the same time, the steady characteristics and the dynamic response performance can be maintained well. Full article

The significance of employing control strategies on a switched reluctance motor (SRM) is that they can reduce vibration noise and torque ripple. With the rapid development of digital system processors, predictive control (PC), as a modern control approach, is increasingly applied to enhance the dynamic performance and operational efficiency of SRMs. This review provides a comprehensive overview of the current state of research on PC strategies of SRMs and classifies PC technologies, such as generalized predictive control (GPC), hysteresis predictive control (HPC), deadbeat predictive control (DPC), and model predictive control (MPC). It summarizes the PC schemes from the aspects of predictive current control (PCC), predictive torque control (PTC), and other PC, and it discusses the current trends in technology development, as well as potential research directions. The insights presented herein aim to facilitate further investigations into predictive control techniques for SRM. Full article