Search Results (1,971)

Based on a fixed-time extended state observer (FESO), this paper proposes a novel predefined performance control (PPC) method for robotic manipulators with false data injection (FDI) attacks and actuator faults. First, a mathematical model of robotic manipulators with parameter uncertainties and external disturbances is constructed. Then, to compensate for the FDI attacks and actuator faults, an extended state is introduced such that the FESO is designed. Moreover, to avoid the transformation from nonlinear constraints to unconstrained variables in PPC, the barrier Lyapunov function (BLF) is introduced. By adopting the novel PPC, tracking errors of the robotic manipulators are driven into a predefined region. Finally, simulations on a two-degree-of-freedom manipulator demonstrate that, compared with FTESO-based sliding mode control, the proposed method has shorter settling times and better tracking accuracy. Full article

Maintaining stable dissolved oxygen (DO) and pH conditions is critical for reliable operation of bioreactor systems used in cell culture and bioprocess manufacturing. However, accurate regulation of DO and pH remains challenging due to nonlinear process dynamics and variations in operating conditions. In particular, temperature fluctuations can affect gas solubility, gas–liquid mass transfer, and CO₂ buffering equilibrium, resulting in deviations in DO and pH. Existing control methods often rely on predefined mechanistic models or reactor-specific parameter identification, which may limit adaptability under changing operating conditions. This paper proposes a disturbance-compensated data-driven adaptive predictive control framework for DO and pH stabilization in bioreactor systems under dynamic temperature disturbances. Based on dynamic linearization, the proposed framework establishes an online input–output representation using measured gas composition, temperature disturbance, and environmental responses. An adaptive gain adjustment mechanism and pseudo-partial-derivative estimation method are developed to update the control relationship online without requiring an explicit process model or iterative optimization. Furthermore, temperature variations are incorporated as measurable disturbances to achieve real-time compensation of their effects on DO and pH dynamics. The proposed framework was evaluated through simulations and experiments using a 3 L bioreactor platform. Compared with a PID controller with temperature feedforward and conventional model-free adaptive predictive control, the proposed method reduced DO and pH tracking errors and improved recovery performance under temperature disturbances. The results demonstrate that the proposed data-driven adaptive predictive control strategy provides an effective approach for DO and pH stabilization in bioreactor systems under temperature-varying conditions. Full article

This paper investigates the predefined-time distributed optimal formation control problem for networked marine surface vehicles (NMSVs) with time-varying optimization objectives and external disturbances. The objective is to drive all vehicles to track the time-varying global optimal trajectory generated by the distributed estimator while maintaining prescribed formation within a predefined time. Accordingly, a hierarchical optimization–formation control framework is developed to bridge global trajectory optimization and local formation control. In the optimization layer, a predefined-time distributed optimization estimator is developed based on local time-varying cost information and neighboring information exchange, which is employed to generate the optimal reference signal. The optimal reference signal is then embedded into the formation control layer, where a tracking controller with a predefined-time segmented terminal sliding-mode surface is designed to compensate for ocean disturbances and ensure accurate trajectory tracking. Lyapunov analysis proves that both the optimization estimation errors and the formation tracking errors converge to zero within a predefined time. Simulation results, including quantitative comparisons, fleets of up to 40 NMSVs, switching and jointly connected graphs, communication impairments, heterogeneous time-varying costs, and rapid references, demonstrate the convergence accuracy, scalability, and practical limits of deadline preservation. Full article

This paper presents a delay-aware observer-side voltage-source inverter (VSI) nonlinearity compensation chain for medium- and high-speed sensorless control of permanent magnet synchronous motors (PMSMs). The method reduces the observer-model voltage mismatch caused by inverter nonlinearities and is implemented with a continuous boundary-layer adaptive-gain sliding-mode observer (ASMO) and a second-order phase-locked loop (PLL). Two-point linear prediction estimates the phase current when the VSI nonlinear voltage error actually takes effect. A $C^1$-continuous cubic zero-crossing weight limits abrupt direction changes near current zero crossings, while a synchronous correlation signal derived from the estimated back electromotive force updates the equivalent distortion-voltage amplitude online. Compensation is applied only to the reconstructed ASMO input voltage, leaving the original current loop and space-vector pulse-width modulation (SVPWM) unchanged. Comparative and ablation simulations show lower characteristic back-EMF harmonics and electrical rotor-position estimation error than conventional compensation. Hardware tests under variable-speed and load-step conditions confirm improved dynamic estimation and disturbance rejection. The intended operating region is medium to high speed, where the back-EMF has sufficient signal-to-noise ratio and a nonsalient machine model is appropriate. The fixed-point realization is reported as implementation-feasibility evidence rather than as the principal contribution. Full article

The inherent nonlinear hysteresis characteristics of giant magnetostrictive actuators are significantly influenced by the frequency of the input signal, and this rate-dependent effect poses severe challenges to high-precision modeling and control. To address this issue, this paper proposes an improved rate-dependent Prandtl–Ishlinskii (PI) model, which incorporates a rate-dependent envelope function with asymmetric left–right thresholds, and additional rate-dependent nonlinear terms to more accurately characterize the frequency-dependent hysteresis behavior of giant magnetostrictive actuators (GMAs). Based on this model, its inverse model is analytically constructed to achieve feedforward compensation, thereby substantially mitigating the influence of hysteresis nonlinearity. On this compensation basis, a sliding mode control strategy with prescribed performance is designed to guarantee global closed-loop stability, and to satisfy the predefined transient and steady-state performance on the tracking error. Finally, verification tests are conducted on a GMA experimental platform, and the results demonstrate that the proposed modeling and composite control scheme can effectively suppress rate-dependent hysteresis disturbances, achieving fast system response and desirable steady-state accuracy, thus validating the feasibility and engineering practicality of the method. Full article

As renewable generation and power-electronic interfaces account for a growing share of power systems, reduced system inertia and weakened voltage support place greater demands on the stable operation of weak and passive networks. This paper proposes a virtual synchronous generator (VSG)-based active support strategy for grid-forming voltage source converter-based high-voltage direct-current (VSC-HVDC) systems. First, the power-balance relationship between the converter station and the synchronous generator is analyzed to establish the basis for VSG control. For active-power–frequency regulation, a virtual zero-error frequency regulation (VZFR) strategy is proposed by introducing an additional power compensation term into the conventional VSG control, improving frequency recovery while retaining virtual inertia and damping. For voltage–reactive-power regulation, the transient voltage support mechanism is analyzed in two stages: the controlled voltage-source characteristic and virtual impedance provide initial voltage support, while the reactive-power–voltage loop subsequently regulates the internal voltage and reactive power output. PSCAD/EMTDC simulations under active load disturbances and different grid voltage sags show that the proposed strategy enhances both frequency regulation and voltage support provided by the VSC-HVDC system. Full article

In maritime navigation, precise and stable ship course control is critical for operational efficiency and maritime safety, yet it is severely challenged by unpredictable marine disturbances (e.g., waves, wind, and currents) that consist of slowly varying and stochastic components. Traditional control methods, though effective under specific operating conditions, exhibit limited adaptability to the nonlinear, time-varying characteristics of marine systems and inherent dependence on accurate ship mathematical models, which easily leads to suboptimal performance and elevated navigation risks, especially under sudden and intense disturbances. To address these limitations, this study proposes a novel control strategy, namely, model-free control integrated with super-twisting sliding mode control (MFSTSMC) with a linear extended state observer (LESO), for enhanced ship course control. Derived from the ultra-local model, the proposed method integrates the simplicity and practicality of model-free control, the real-time disturbance estimation and compensation capability of LESO, and the strong robustness of STSMC. The Lyapunov stability theory is rigorously employed to prove the stability of the entire control system, ensuring that the steady-state error converges to zero. Comparative analyses are conducted on an ocean ship verification platform, with strictly unified parameters for fairness. The comparative results evaluate the proposed method under three typical scenarios: course-keeping (small ±10° and large ±70° maneuvers), course tracking (low/high-frequency sinusoidal trajectories and high-frequency 20° abrupt change trajectory), and resistance to sudden escalating disturbances. The results demonstrate that the proposed MFSTSMC with LESO significantly outperforms existing controllers in terms of tracking accuracy, response speed, stability, and disturbance rejection capability. Its superior performance originates from the synergistic effect of real-time disturbance compensation and robust sliding mode compensation, which effectively mitigates the impact of model deviations and complex marine disturbances. This study provides valuable insights for the development of advanced marine navigation control strategies, and the proposed method exhibits promising engineering application prospects for ocean ship navigation in complex dynamic marine environments. Full article

Conventional sinusoidal sweep methods are time-consuming, especially in the low-frequency region, which limits their application in rapid and online battery condition monitoring. Moreover, under practical operating conditions, low-frequency drift, operating disturbances and limited observation windows further deteriorate impedance extraction accuracy. This paper proposes a rapid wide-band impedance measurement method for lithium-ion batteries based on three-level excitation. First, a three-segment three-level excitation strategy was developed by performing frequency-band partitioning, target frequency point configuration, and discrete frequency grid matching, enabling efficient frequency-domain resource allocation within a limited test duration. To improve the reliability of impedance estimation under operating disturbances, a low-order drift model and a multi-window redundant observation framework were established to decouple the impedance response from slowly varying drift components. Furthermore, a residual compensation method combining physical constraints with a Shallow Recurrent Decoder-based Reduced Order Model (SHRED-ROM) is proposed to correct low-frequency residual errors. Experimental results demonstrate that the proposed method can acquire a broadband impedance spectrum over 0.01 Hz–1 kHz within 179 s, achieving RMSE values of 0.436 mΩ and 0.474 mΩ for the full frequency band and low-frequency region, respectively. Under equivalent constant-voltage charging conditions, the proposed method reduces the impedance magnitude error at 0.01 Hz from 48.59 mΩ to 3.43 mΩ and decreases the phase error from 23.95° to 7.09° compared with the multi-sine excitation method. The proposed method also maintains high measurement accuracy under operating disturbances, demonstrating improved robustness for low-frequency impedance acquisition. These results indicate that the proposed approach provides an effective solution for rapid broadband EIS measurement and online condition monitoring of lithium-ion batteries. Full article

The inherent dynamic hysteresis nonlinearity of piezoelectric actuators severely degrades the control accuracy of micropositioning systems. This paper proposes a composite control method based on a phase compensator and polynomial correction. Unlike conventional approaches that rely on hysteresis modeling and inversion, the proposed method equivalently treats the symmetric hysteresis of piezoelectric actuators as a phase-lag property of the system and employs a phase compensator to achieve feedforward compensation. For asymmetric hysteresis, a polynomial is cascaded with the phase compensator to correct the amplitude discrepancy between ascending and descending branches, effectively overcoming the inability of the phase compensator alone to accommodate asymmetric nonlinearity. This strategy circumvents the cumbersome procedures of precise hysteresis modeling and parameter identification, offering a simple structure, few parameters to be identified, and convenient engineering implementation within the investigated operating range. To further enhance disturbance-rejection capability and steady-state positioning accuracy, the phase–polynomial feedforward compensator is combined with PI feedback control, establishing a composite feedforward–feedback architecture for high-performance piezoelectric actuator control. Feedforward compensation and composite control experiments validate the effectiveness of the proposed method. Full article

Electric pump-fed liquid rocket engines require coordinated propellant delivery under coupled hydraulic, electrical, actuator, and thermal constraints. This study develops an integrated reduced-order model of a dual-channel electric pump-fed propellant system, including the battery and DC bus, power converters, two independently driven motor–pump units, hydraulic feed lines, control valves, combustion chamber, and thermal states. A hierarchical constrained multi-criteria supervisory controller is formulated to regulate chamber pressure, oxidizer-to-fuel mixture ratio, feed-channel coordination, electrical loading, and thermal response. Performance is compared with a conventional PI controller and an enhanced PI configuration incorporating feedforward and disturbance compensation under nominal, degraded, long-duration, and constraint-active scenarios. Relative to the baseline PI controller, the proposed controller reduced the startup pressure peak from 2.64 to 2.32 MPa, pressure RMSE from 0.016 to 0.006 MPa, and mean branch synchronization error from 0.112 to 0.028 MPa. The minimum battery voltage increased from 87.0 to 90.4 V, while the peak motor current decreased from approximately 88 to 65 A. In the 1800 s thermal case, the maximum fuel-drive temperature decreased from approximately 104 to 74 °C. Numerical verification and comparison with published experimental benchmarks supported the physical plausibility and equilibrium-scale behavior of the reduced-order model, while differences in absolute transient time scales limit its use for quantitative prediction of hardware transient dynamics. The results indicate improved coordinated control within the investigated operating envelope and support the use of the framework for comparative system-level assessment and preliminary design of small-class electric-pump propulsion systems. Full article

Accurate reducer noise prediction is essential for condition monitoring and predictive maintenance of mechanical transmission systems. However, the strong nonlinear coupling between operating conditions and noise responses, together with measurement uncertainties, remains a major challenge for data-driven prediction methods. This study proposes a hybrid prediction framework integrating feature selection, adaptive neural modeling, and residual compensation to improve the accuracy of planetary winch reducer noise prediction. A random forest (RF)-based feature selection strategy is first employed to identify the most informative vibration characteristics associated with reducer noise. Subsequently, a generalized regression neural network (GRNN) optimized by a hybrid whale optimization and bat algorithm (WOA-BAT) is developed to adaptively determine the smoothing factor and enhance nonlinear prediction capability. Furthermore, a residual Kalman compensation (RKC) mechanism is introduced to suppress prediction fluctuations caused by stochastic disturbances and modeling uncertainties. Experimental results demonstrate that the proposed WOA-BAT-GRNN-RKC framework achieves highly accurate noise prediction, with an RMSE of 0.05631 dB and an MAE of 0.027972 dB. The corresponding MAPE is 0.037897%. The proposed approach provides an effective pathway toward intelligent reducer condition monitoring and predictive maintenance. Full article

Underwater glider (UG) formations exhibit significant trajectory deviations when subjected to non-uniform ocean currents, complicating spatial reconfiguration upon exiting complex marine environments and compromising environmental monitoring fidelity. To solve these problems, we develop a rapid formation reconfiguration algorithm based on distributed model predictive control (DMPC). The algorithm combines a flexible boundary-triggering mechanism for autonomous control suspension and rapid activation, a nonlinear vector heading pre-compensation scheme to counteract strong current disturbances, and a multi-objective leader capability assessment with a dynamic rotation strategy for optimized leader selection. The predictive plant model is calibrated utilizing empirical sea trial datasets, and its control performance is validated through comparative simulations against conventional MPC and active disturbance rejection control (ADRC). The results demonstrate that the proposed algorithm reduces the standard deviation of lateral inter-glider distance by 42% and 17% relative to ADRC and conventional MPC, shortens the reconfiguration time to 13.3 h, and lowers the maximum relative deflection, lateral distance standard deviation and average energy consumption. This framework significantly improves formation stability, reconfiguration efficiency, and energy efficiency, providing a robust methodology for persistent swarm deployments. Full article

Tracked vehicles operating in hilly and mountainous agricultural environments are frequently subjected to pitch, roll, and vibration, which can introduce time-varying errors into ultra-wideband phase-difference-of-arrival (UWB-PDOA) relative localization. Aiming to improve localization accuracy under such disturbances, this study proposes a relative localization error compensation method that integrates long short-term memory (LSTM) residual learning with a residual-adaptive extended Kalman filter (RAEKF), referred to as LSTM-RAEKF. The proposed method combines UWB-PDOA measurements with inertial measurement unit information to learn disturbance-related localization residuals and adaptively compensate for relative position and theta observations before filtering. A UWB/IMU relative localization test bench was developed, and experiments were performed under static, pitch, roll, and vibration conditions. Across different fixed-point tests, the proposed method reduced the planar position RMSE and theta RMSE by 35.0–62.9% and 54.7–70.8%, respectively. Considering all experimental conditions, the position RMSE decreased from 4.00 cm to 1.81 cm, while the theta RMSE decreased from 5.64° to 2.17°, corresponding to reductions of 54.8% and 61.5%, respectively. Furthermore, LSTM-RAEKF outperformed the standard extended Kalman filter and the innovation-based adaptive estimation extended Kalman filter. Overall, these results demonstrate that LSTM-RAEKF can effectively suppress localization errors induced by attitude disturbances and provide stable relative localization information for subsequent tracked vehicle following control. Full article

The increasing demand for electrified rail transportation has intensified power quality (PQ) challenges, including harmonics, voltage imbalance, and low power factor (PF). These issues have driven the development of advanced traction power supply systems, particularly co-phase configurations, to improve power quality, enhance grid-connected stability, and strengthen the operational resilience of railway power infrastructure. This paper proposes a co-phase power supply system for high-speed railways that facilitates high-speed train operation by integrating power quality compensation technologies while reducing the required number of neutral sections by half, thereby improving the continuity and robustness of traction power delivery. To address PQ issues, a capacitive-coupled hybrid power quality conditioner (HPQC) incorporating renewable energy sources (RESs) into its DC link is introduced. Given the highly dynamic and time-varying nature of railway loads, a sliding mode control (SMC)-based robust control method is developed based on the state space model of the co-phase power supply system and the HPQC to provide a stable and rapid response to load variations and operational disturbances. The effectiveness and real-time implementation capability of the proposed approach are validated through real-time control hardware-in-the-loop (CHIL) simulations. Results from MATLAB/Simulink simulations and real-time CHIL testing demonstrate substantial harmonic reduction, improved power factor, reduced negative-sequence currents, and enhanced overall system efficiency. These outcomes confirm the suitability of the proposed system for modern high-speed railway applications and highlight its contribution to resilient traction power supply systems capable of maintaining reliable operation under highly variable loading conditions. Full article

Residual vibration of industrial manipulators can limit positioning efficiency and dynamic accuracy during high-speed motion. This study develops an integrated vibration-suppression framework for a rigid-link manipulator with flexible-joint dynamics. A controller-oriented rigid–flexible model with lumped disturbances is established, and a disturbance observer (DOB) is employed as the inner-loop compensation layer under a small-gain robustness constraint. On the compensated nominal model, partial eigenstructure assignment (PESA) selectively increases the damping of the retained flexible modes while preserving the rigid-body eigenstructure associated with trajectory tracking. A pose-dependent gain-scheduling mechanism further updates the PESA feedback gain to accommodate configuration-dependent modal-frequency variation. Numerical comparisons with conventional PID, standalone DOB, and standalone PESA demonstrate improved residual-vibration attenuation and settling behavior. Hardware tests on an Aubo i5 manipulator, with 16-channel responses directly acquired under the respective control configurations, further show an approximately 80% reduction in the representative low-frequency vibration amplitude relative to the PID baseline under the considered operating condition. Full article