A robust model predictive current control (MPCC) strategy is proposed for motor drive systems, in which a cascaded architecture is innovatively constructed by integrating a noise-resilient augmented observer (NAO) with an adaptive data-driven iterative harmonic identification (ADIHI) mechanism. First, to address dominant aperiodic disturbances in the ultralocal motor model, an enhanced NAO is developed, where the integral of noisy measured current is deliberately introduced as an augmented state variable. This novel augmented state effectively decouples the adverse interaction between high observer gains and high-frequency current measurement noise, enabling inherent low-pass filtering properties of the integrator operator and significantly improving noise immunity without sacrificing the disturbance estimation accuracy. Second, based on the NAO-estimated disturbances and ultralocal model, a high-pass-filtered harmonic internal model component is extracted and further refined through the proposed ADIHI scheme. By incorporating an adaptive forgetting factor and an iterative identification mechanism, ADIHI achieves accurate online harmonics extraction. Moreover, an adaptive forgetting factor updating strategy driven by the variation rate of harmonic identification error is designed to enhance robustness against operating condition variations. Finally, the overall closed-loop system stability of the proposed MPCC framework is rigorously established using the Nyquist stability criterion. Explicit analytical expressions for control parameters are derived under stability constraints, and systematic stability regions and parameters tuning guidelines are provided. Extensive experimental results on a motor test bench demonstrate the effectiveness and superiority of the proposed current control strategy.

This research tackles motion inaccuracies in multiaxis maglev planar motor (MPM) systems, crucial for precision applications such as semiconductor lithography, which suffer from position-dependent disturbances and multiaxis coupling. The objective is to develop a model-data fusion disturbance suppression framework. Our methodology integrates a static decoupling model, derived from electromagnetic and mechanical analysis, to enable independent control of four motion degree of freedom (DOF) x, y, z, Rx . A multi-DOF feedforward compensation using a harmonic disturbance model addresses identified low-frequency, periodic disturbances by exploiting their spatial position dependency, overcoming limitations of conventional observers. Finally, a radial basis function neural network (RBFNN) approximates and mitigates residual nonlinear disturbances. Key findings demonstrate the framework's efficacy: the decoupling model reduces multiaxis crosstalk, and harmonic feedforward attenuates periodic disturbances. The RBFNN-based residual compensation significantly enhances tracking accuracy and has been experimentally verified under different motion conditions. This work contributes a high-performance disturbance suppression solution for precision mechatronic systems.

Conventional motor drives are subjected to extensive disturbances and uncertainties across entire frequency spectrum, which significantly deteriorate current control performance within electric propulsion system. To address this issue, this paper proposes a discrete-time composite control strategy that integrates an improved equivalent-input-disturbance (IEID) approach with a dynamic decoupled adaptive damping (DDAD) regulator, aiming to suppress external disturbances and improve the transient current response. Specifically, a proportional-integral augmented observer (PIAO) is introduced into the IEID framework, where the integral of the measured current is treated as an augmented variable. This modification enhances both the estimation accuracy of internal states and the system’s resilience to the current measurement noise. Furthermore, a modified causal filter, constructed building upon an integral-resonant internal model structure, is incorporated into the IEID estimator to achieve simultaneous and effective attenuation of both disturbances and harmonics. Finally, an improved adaptive damping function that is adjustably updated with load current as well as motor speed and the associated dynamic decoupled control law are systematically designed using poles placement techniques, enabling the superior transient dynamics and the flexible damping characteristics. Comparative experimental results validate the practical applicability of the proposed control method.

The n-coil (n+1)-leg inverter serves as a key hardware solution for independent-coil-based permanent magnet linear synchronous motors (ICPMLSM) due to its simple circuit structure. However, the demand for independent drive of each coil under asymmetric phase quantities makes most conventional modulation strategies inapplicable. Meanwhile, the research on the modulation strategy for output current harmonic suppression based on this inverter is still lacking. This paper proposes a carrier-based modulation strategy for the n-coil (n+1)-leg inverter. By zero-sequence voltage injection to all legs, each coil is decoupled from the auxiliary leg, enabling independent drive. Instead of treating zero-sequence voltage injection as a waveform-shaping technique, it is reformulated as a system-level harmonic minimization problem. A harmonic metric is derived and the optimal zero-sequence voltage is obtained by minimizing the aggregated harmonic content of all energized coils, applicable to arbitrary quantity of energized coils. The DC-link utilization under different quantities of energized coils is analyzed, revealing an inherent trade-off between harmonic suppression and linear modulation range. Furthermore, robustness of the proposed method is also analyzed. Finally, the effectiveness of the proposed method is verified by detailed experiments under different quantities of energized coils.

Classical current control strategies in electric propulsion systems often suffer from degraded performance under periodic and aperiodic disturbances. To overcome these limitations, this paper proposes a novel current control framework that combines an adaptive fractional-order resonant controller (AFRC) with a fixed-time augmented extended state observer (FxTAESO), aiming to enhance disturbance rejection and dynamic robustness. Firstly, the proposed AFRC introduces a self-tuning fractional-order operator, which adaptively adjusts in real-time according to load current, harmonic rejection strength, and desired phase margin. This adaptive mechanism enables precise harmonic compensation while ensuring stability and robustness across the varying operating conditions. Subsequently, the FxTAESO incorporates a current integral term as system augmented variable to decouple the coupling effect between current measurement noise and high observer gains. Additionally, by embedding an improved nonlinear fixed-time convergence law, the observer ensures that the estimation error converges to a bounded neighborhood of the equilibrium point within a predetermined time, independent of initial conditions. Finally, experimental validation on a PMSM drive platform demonstrates that the proposed FxTAESO-AFRC scheme achieves superior steady-state accuracy, faster transient response, and stronger disturbance suppression compared to conventional methods.

Interleaved auxiliary-commutated resonant-pole (ACRP) inverters are used for high-precision DC–AC conversion. However, direct application of steady-state carrier phases at start up may give different units unequal first conduction intervals, causing start-up inrush current. This article analyzes the start-up inrush mechanism and proposes a soft start-up strategy based on carrier phase control. First, the relationship between the first conduction interval and the switch current peak is derived to clarify the origin of the start-up inrush current. Then, the passive current sharing after start-up is described using switching-cycle averaging, and the synchronization interval before carrier phase restoration is determined. In the proposed strategy, the corresponding carriers of the interleaved modules are first aligned so that all units start with the same first conduction interval. The carrier phases are then restored to their steady-state interleaved positions under the switch current limit. Experiments on a 300 V, 250 kHz prototype show that the peak switch current is reduced from approximately 20 A under direct start-up to the 10 A steady state envelope. The complete soft start-up process is finished within 0.2 ms. The measured passive current-sharing time constant agrees with the calculated value within 2.38%, and tests under resistive and resistive–inductive (R–L) loads verify the effectiveness of the proposed strategy.

Agile earth observation satellites employ multiple actuators to enable flexible and responsive imaging capabilities. While significant advancements in actuator technology have enhanced satellites' torque and momentum, relatively little attention has been given to control strategies specifically tailored to improve satellite agility. This paper provides a comparative analysis of different Model Predictive Control (MPC) formulations and introduces an augmented-MPC method that effectively balances agility requirements with hardware implementation constraints. The proposed method achieves the high-performance characteristics of nonlinear MPC while preserving the computational simplicity of linear MPC. Numerical simulations and physical experiments are conducted to validate the effectiveness and feasibility of the proposed approach.

This article is concerned with stability analysis and observer-based control synthesis for a class of discrete-time switched linear systems with limited statistical information. Instead of commonly studied switching signals such as dwell-time (DT) or Markov chain, a more general class of switching signals, random mode-dependent persistent sojourn-time (RMPST) switching, is investigated. It is composed of fixed parts with no mode switching, random parts without distribution restrictions, and intervals where arbitrary switching is allowed. To tackle the challenges posed by inaccessible modes, unknown transition probabilities, and partially unknown sojourn-time distribution, stability analysis is performed via constructing a Lyapunov function tailored to accommodate the characteristics of RMPST switching. The proposed Lyapunov function is not only mode-dependent but also elapsed-time and quasi-time dependent during fixed-random parts and arbitrary switching intervals, respectively. By means of the new Lyapunov function, an observer-based control approach is introduced for underlying switched systems, and criteria for the existence of observers and controllers are established with the set of admissible switching signals. A novel algorithm is also developed to solve the existence condition by extending the traditional cone complementary linearization (CCL) technique. The effectiveness and applicability of the theoretical results are revealed by a practical space robot manipulator system.

The independent-coil-based permanent magnet linear synchronous motor (ICPMLSM) has great flexibility due to the minimum unit control, and it plays an important role in advancing industrial automation. However, research on its modeling and current control is still limited. This article presents a comprehensive study on both aspects. First, general linear models of inductance and back electromotive force (EMF) are established under different coupling conditions between the mover and the coils. Based on the principle of constant electromagnetic thrust, a current distribution strategy is developed, and a minimum-distance current switching strategy is further derived through the calculation of current zero-crossing points. Considering parameter variations under different coupling states, a model-free predictive current control (MFPCC) strategy is adopted to ensure robust current regulation. Furthermore, a model-free adaptive feedforward (AFF) controller is integrated into the MFPCC, forming an adaptive MFPCC (AMFPCC). This enhanced control scheme enables real-time compensation of both back EMF and resistive voltage through online parameter adaptation. Finally, the proposed control strategies are experimentally validated. The results confirm the effectiveness of the current distribution and switching methods and demonstrate that the AMFPCC achieves near-zero steady-state current error while exhibiting strong robustness.

The transition to electric propulsion systems in aviation is a key trend toward achieving higher efficiency, reduced fuel consumption, and lower maintenance costs, while significantly reducing the carbon footprint of aircraft. Medium-voltage dc distribution has emerged as an effective solution. This article explores the application of the seven-level converter in aircraft electric propulsion systems. It provides a detailed analysis of its operating modes and modulation principles, and based on these insights, proposes an improved modulation strategy to reduce losses and optimize system efficiency. Furthermore, a comprehensive loss model of the converter topology is developed. Loss evaluations based on this model indicate that the 7L topology, which integrates Si-IGBTs and SiC-mosfets in a hybrid device solution, achieves lower losses while balancing cost-effectiveness, ultimately attaining an efficiency exceeding 97% . Compared to conventional ANPC-based solutions, this approach offers significant performance advantages. Specifically, compares and analyzes the efficiency and loss distribution of two drive solutions, providing a valuable reference for engineers and researchers in the future development of electric aircraft propulsion systems.

This article proposes an optimized real-time commutation algorithm aiming to achieve high-precision force/torque decoupling as much as possible while preventing the coil current amplitude and its slew rate from exceeding predefined limits. First, an electromagnetic force/torque and coil array current commutation model is established for the studied concentric winding moving-coil Maglev planar motor (CWMPM), along with a complete decoupling control method. Next, an improved commutation algorithm based on active set algorithm (ASA) was proposed, and its performance differences with traditional pseudoinverse (PI), fast iterative peak shrinkage algorithm (FIPSA), and redistributed pseudoinverse (RPI) were analyzed through simulation in terms of electromagnetic force/torque decoupling error, current amplitude and its slew rate, iteration computation, and power loss and its uniformity. Finally, real-time closed-loop servo control is implemented on the constructed CWMPM prototype platform using all of the aforementioned current commutation methods. Experimental results demonstrate that the proposed algorithm achieves precise electromagnetic force/torque decoupling while effectively limiting current amplitude and its slew rate, and avoids excessive computational resource consumption, which has significant practical engineering value.

High-precision linear propulsion systems require power amplifiers (PAs) that simultaneously provide ultra-low current distortion and high-bandwidth current tracking. However, in conventional switched PAs, dead-time effect and current zero-crossing distortion severely degrade current linearity, while existing controller tuning approaches often fail to explicitly balance closed-loop peaking, robustness, and bandwidth in digitally implemented high-frequency systems. To address these challenges, this paper proposes a high-precision switched PA featuring two coordinated innovations at both the power stage and control stage. First, an auxiliary-current commutation mechanism is introduced into the switched PA so that the MOSFET current is forced to reverse in every switching period. As a result, dead-time effect and current zero-crossing distortion are eliminated at the source, while ZVS-ON is achieved and the equivalent switching frequency is increased. Second, to fully exploit the improved power stage, a weighted multi-objective controller parameter tuning method is proposed. The method establishes a discrete-time current-loop model consistent with the practical implementation and jointly constrains the closed-loop peak, phase margin, sensitivity, complementary sensitivity, and bandwidth, so as to achieve a balanced tradeoff between tracking accuracy, dynamic response, and robustness. Experimental results verify an equivalent switching frequency of 1 MHz, a minimum current THD of 0.03%, a closed-loop tracking error within 0.34dB below 10kHz, and a maximum achievable bandwidth of 14kHz. These results demonstrate that the proposed PA provides a practical solution for precision-oriented linear propulsion applications requiring both ultra-low distortion and high dynamic current tracking.

To enhance the triaxial contour trajectory tracking performance of maglev planar motors (MPMs), this article proposes an analytical contouring error estimation (CEE) method based on third-order Taylor expansion and designs a contouring error controller (CEC) using the fixed-time high-order sliding mode (FxT-HOSM) algorithm with modified feedback. Initially, a state-space model of the MPM incorporating concentrated disturbances in each degree of freedom (DOF) is derived using a static decoupling control algorithm. Subsequently, accounting for the curvature and torsion of 3-D reference trajectories, a third-order Taylor expansion-based CEE algorithm is introduced to enable accurate real-time estimation and compensation. Furthermore, the CEC design based on the FxT-HOSM principle comprises: 1) a nonsingular fixed-time sliding surface (NFxTSM); 2) a fixed-time high-order reaching law; 3) a fixed-time contouring error differentiator; and 4) a fixedtime disturbance observer. This combination ensures highprecision contour tracking while mitigating chattering. Ul-timately, experimental results under various spatial trajectories with varying curvature and torsion confirm that the proposed FxT-HOSM controller achieves excellent performance in both contouring and tracking errors.

To effectively suppress the composite disturbances in a six-degree-of-freedom magnetic levitation micro-motion stage, this paper proposes a disturbance compensation strategy based on a bandwidth-adaptive cascade linear extended state observer. First, a static decoupling algorithm is employed to establish independently controllable state-space equations for each degree of freedom, and the components of the composite disturbances in each axis are analyzed. Subsequently, to achieve higher-order disturbance compensation, a cascade linear extended state observer is designed to estimate and compensate for the lumped disturbances in each degree of freedom. Moreover, to balance dynamic disturbance rejection with static noise sensitivity, a bandwidth-adaptive mechanism is introduced to dynamically adjust the observer bandwidth. Finally, both simulation and experimental results are provided to validate the superiority of the proposed approach.

Compared with the voltage source inverter-fed (VSI-fed) induction motor drive, the current source inverter-fed (CSI-fed) induction motor (IM) drive can protect systems from overcurrent and short circuits and has a higher filtering characteristic. However, the generation method of switching signals for the CSI is different from that for the VSI, and the action modes of the switching tubes change with the sectors. In addition, due to the filtering capacitor parallel connected with the IM, the order of the AC-side system increases, which increases the complexity of the modulation and control schemes for the CSI-fed IM. In this paper, the vector composition and sector distribution formed by the switching states are analyzed. On this basis, SVPWM modulation without an additional hardware logic conversion circuit is proposed, and its implementation process is presented. Then, the control system, which contains the voltage proportional inner loop and the current proportional–integral outer loop, is designed for the CSI-fed IM, and the principle of parameters tuning is presented in detail. Finally, simulation models and experimental results are established, and the correctness of the modulation scheme implementation process and the effectiveness of the control system presented in this paper are verified.

Nonlinear friction force is the predominant force disturbance in permanent-magnet linear synchronous motor (PMLSM) with guide rails, and it would worsen position control precision, especially during motion reversals (velocity zero-crossing). To minimize the effect of nonlinear friction on position accuracy in the reciprocating motion for PMLSM, a compensation scheme which consists of a iterative learning-based bang-bang compensator (ILBBC) and a generalized proportional-integral observer (GPIO) is presented in this paper. ILBBC is utilized to compensate for abruptly changing Coulomb friction force in velocity zero-crossing, and GPIO is added to enhance compensation performance for vicious friction force. To effectively merge ILBBC and GPIO, three-stage compensation scheme is proposed, thus, the combination of ILBBC and GPIO is capable of compensating for nonlinear friction in both velocity zero-crossing and non-zero regions. Design and stability of ILBBC and GPIO are theoretically analyzed. Finally, comparative experiments which include no compensation, GPIO-based compensation, and ILBBC + GPIO compensation are implemented under two kinds of sinusoidal position trajectories to demonstrate the effectiveness of the proposed compensation scheme.

Modern flexible production lines and intelligent logistics systems require position sensing solutions that support long travel ranges, high accuracy, cable-free operation, and minimal structural constraints. Conventional high-precision encoders, such as optical gratings, suffer from high cost and limited range, while magnetic encoders are typically restricted to short-travel applications and constrained by cable connections. This paper presents a long-range absolute position sensing method based on an anisotropic magnetoresistance (AMR) sensor array. A primary sensor index is first identified to locate the position within a specific magnetic period. Then, the actual position is reconstructed using an arctangent algorithm applied to the sinusoidal output signals. To address position discontinuities caused by magnetic field distortions near array edges, a compensation algorithm is proposed to ensure continuity and accuracy of the absolute position output. Experimental results validate the effectiveness of the method, demonstrating high accuracy over long travel distances, as well as suitability for cable-free and structurally flexible industrial applications.

The integration of demand response (DR) and energy storage systems in electro-thermal systems has emerged as a cornerstone for advancing energy sustainability, enabling the transition to renewable-dominant grids while balancing economic and operational constraints. This paper constructs a planning model for the electric-thermal coupled microgrid, considering multiple operational safety constraints, and transforms the model into a mixed-integer linear programming problem using an appropriate method. Simulation results validate the effectiveness of the proposed approach, and the economic performance is significantly improved.

Dual three-phase permanent magnet synchronous machine (DTP-PMSM) suffers from the disadvantage of easily occurring large stator current harmonics under inverter nonlinearity, non-sinusoidal back-electromotive force, and external disturbances. To deal with the problem, an improved generalized extended state observer (IGESO) for current harmonic suppression is proposed in this paper. Firstly, the relationship between the observation of low-frequency and high-frequency periodic disturbances in conventional disturbance observers is explored. Secondly, a notch filter is used to optimize the conventional generalized extended state observer (GESO) structure to avoid interference in observing two different frequency disturbances. Then, a novel observer poles design principle is proposed, which can control the suppression frequency range and attenuation of periodic disturbances respectively. Besides, the performance compared with other strategies and the stability analysis of IGESO in the discrete-time domain are presented. The parameter range for system stability is also provided. Finally, the proposed method is evaluated on a laboratory DTP-PMSM platform.