Search Results (79)

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

Non-target organisms are not well studied. The objective of this work was to evaluate the effect of seven essential oils, two fixed oils, d-limonene and eugenol on the mortality, behavior and infectivity of entomopathogenic nematodes (ENPs). The oils were diluted at 1% (v/v) in water with Tween^® 80 PS at 0.05% (v/v), and water with Tween^® alone was used as the control treatment. In the mortality test, 2 mL of solution containing 50 µL of the nematode suspension, 20 µL of oil/compounds solution isolated with Tween 80, and 1930 µL of water were placed in plastic containers. After four days, the number of dead juveniles was counted. In the bioassay of the behavior of the EPNs, the frequency of lateral body beats of the infective juveniles in liquid medium was analyzed after exposure to the solutions. In the infectivity test, after contact of the EPNs with oils and essential oil chemical compounds, the juveniles were washed and applied to second-instar Spodoptera eridania larvae. All oils and isolated compounds caused mortality in H. amazonensis and S. rarum, with Ocimum canum and the isolated compound eugenol showing the highest efficacy against H. amazonensis and O. canum, Eucalyptus citriodora, Zingiber officinale, Salvia sclarea and the isolated compound eugenol being the most effective against S. rarum. There was a reduction in the number of lateral beats of H. amazonensis and S. rarum for all treatments, with the exception of Cymbopogon winterianus in H. amazonensis and Annona muricata in S. rarum. The infectivity of H. amazonenis and S. rarum on S. eridania was reduced when exposed to the solutions, with the exception of the isolated compound d-limonene in both species, soursop for H. amazonenis and rosemary for S. rarum, which were classified as non-toxic to the species tested. The results obtained in this study may be useful for the choice of oils and essential oil chemical compounds with potential use in integrated pest management programs. 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

In order to improve the dynamic response and disturbance rejection performance of electric machines, a deadbeat predictive speed control (DPSC) scheme for a permanent magnet synchronous motor (PMSM) is proposed. To begin with, a DPSC controller was proposed with the purpose of achieving precise control for the next control cycle, and the control parameters were determined based on the optimal parameter design method. For better application, performance comparisons were made with a conventional PI control, and the mismatch effects of inertia and torque were analyzed. In order to improve the disturbance rejection performance of the system, an extended sliding mode observer (ESMO) was constructed to compensate for disturbances. Experimental verification with a conventional PI control indicates that the proposed DPSC control can reduce the speed response time from 0.675 s to 0.650 s. When the electric machine operates stably and is applied to a torque disturbance of 0.4 Nm, the speed fluctuation and settling time can be reduced from 9 rpm and 1.7 s to 6 rpm and 0.5 s, respectively. This proposed method effectively enhances the speed control performance of PMSM and can be applied to high-performance electric machine applications. 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

This paper presents the development, control, and experimental validation of a novel bipedal robot with a passive tendon. The robot, featuring foldable legs, coaxial actuation, and compact folded size, is endowed with a leg configuration with a five-bar mechanism. Based on biological observations of human walking, a passive artificial tendon made of emulsion is fabricated to work in conjunction with a tensioning device, providing adaptive heel touchdown and toe push-off in sync with single-leg movement. The tailored control framework for the bipedal robot is further established with the double-layer architecture. The regulation layer employs the linear inverted pendulum (LIP) model to generate reference trajectory of the center of mass (CoM) with a dead-beat style of parameter adjustment. An inverse-dynamics-based whole-body controller (WBC) is applied to enforce the full-order dynamics of the bipedal robot to reproduce the LIP model’s behavior. We carry out the experiments on the physical prototype to evaluate the walking performance of the developed bipedal robot. The results show that the robot achieves stable walking at the speed of 0.8 m/s (almost twice the leg length/s) and exhibits robustness to external push disturbance. 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