Search Results (416)

This paper presents a robust attitude-tracking control architecture for rigid spacecraft subject to model mismatches and external disturbances. Quaternions are utilized for attitude representation to prevent the gimbal lock associated with Euler angles. While conventional nonlinear dynamic inversion (NDI) relies on Newtonian mechanics and input–output linearization—which inadvertently generates internal zero dynamics and encounters severe control derivative discontinuities at the q₀ = 0 singularity—this study proposes a novel NDI framework derived strictly from Udwadia’s Lagrangian formulation. This approach realizes an exact input-state linearization directly on the 6-degree-of-freedom active holonomic constraint manifold, completely eliminating internal zero dynamics and mathematical singularities. To ensure robustness against physical uncertainties, the singularity-free NDI is augmented with a nonlinear disturbance observer (DOBC) and an outer-loop linear quadratic (LQ) tracking controller. A rigorous composite Lyapunov stability analysis is conducted for the complete closed-loop architecture. The analysis formally guarantees that both the isolated disturbance estimation error and the fully interconnected dual-loop NDI-DOBC system are Uniformly Ultimately Bounded (UUB), even in the presence of realistic, time-varying disturbances with non-vanishing derivatives (\({ \boldsymbol {\dot{d}} \neq \textbf{0}}\)). Comprehensive numerical simulations, parameterized by a physical spherical air-bearing testbed subject to state-dependent gravitational imbalance torques, validate the architecture’s exceptional tracking precision, smooth transient response, and robust disturbance rejection. Full article

A Lyapunov-based framework for stability analysis and synthesis of adaptive neural-network (NN) controllers for a class of uncertain second-order nonlinear systems (SNS) with bounded external perturbations and unmodelled dynamics is presented. Online learning is employed for the reconstruction of the plant nonlinearity with the use of a radial-basis-function (RBF) network whose weights are adapted using a direct adaptation law deduced from a single composite Lyapunov function. The proposed controller couples the weight update to a persistent robustifying action, while the closed-loop stability is guaranteed throughout the learning transient, in contrast to schemes that guarantee stability after learning has converged. Using a composite Lyapunov function in the filtered tracking error and the weight-estimation error, we prove that all closed-loop signals are uniformly ultimately bounded (UUB) and that the tracking error converges to an explicitly characterized residual set whose radius is governed by the network reconstruction accuracy, the disturbance bound and the design gains. A $\sigma$-modification ensures parameter boundedness without persistency of excitation, and a robustness theorem shows that bounded parametric perturbations of the plant preserve stability and enlarge the ultimate bound only gradually (a graceful degradation, rather than a loss of the guarantee). The open-loop plant (a forced double-well Duffing oscillator) is characterized by means of equilibrium and Jacobian analyses. A bifurcation diagram and the largest Lyapunov exponent are presented, which show a chaotic regime (with ${\lambda }_1\approx 0.17$). Numerical experiments indicate that the proposed controller is able to suppress the chaotic motion with a small value of the ultimate bound, and maintain a smooth reference motion with a small and constant RMS error of order ${10}^{-3}$, which is approximately 26 times less than the RMS error obtained with a tuned fixed-gain baseline, and the theoretical dependence of the ultimate bound on the disturbance and the design gains is confirmed by sensitivity sweeps. Full article

Cooperative adaptive cruise control (CACC) platoons rely on Vehicle-to-Vehicle communication and GPS to maintain sub-second headways, creating cyberattack surfaces underrepresented in standard surrogate-safety metrics. We built a fully equation-based, Routh–Hurwitz- and Lp-string-stability-verified simulation of a ten-follower (eleven-vehicle, including the leader) CACC platoon (point-mass dynamics, actuator lag, PD spacing control) and subjected it to a two-channel GPS-spoofing attack corrupting both the attacked vehicle’s control loop and its broadcast position; velocity and acceleration broadcasts, and the CACC feed-forward term they drive, are left uncorrupted, so the reported boundaries are conditional on this restricted, single-channel threat model and should be read as a lower bound on attack severity rather than a worst case. Across a 64-cell severity–duration grid (2–20 m, 1–10 s; h = 0.6 s), minimum time-to-collision fell from 31.7 s to a simulated collision in 6/64 cells (9.4%), driven more by magnitude than duration; the disturbance decays sharply after the first hop rather than cascading down the platoon, so the resulting risk is local, not cascading. A 48-cell headway grid showed h ≥ 0.7 s eliminated all collisions at the originally tested attack duration (3/8 → 0/8 at fixed severity), a result that held under two alternative controller-gain sets tested for sensitivity and was largely, though not universally, robust to a substantially stiffer third set. A position sweep found risk invariant across nine of ten platoon positions. Batch-computed first-hop propagation and tail-to-origin amplification ratios showed the disturbance transiently amplifies (ratio > 1) at its first hop in a third of tested attacks despite decaying three orders of magnitude by the platoon’s tail, a behavior distinct from the front-injected Lp string stability verified separately. Peak root-mean-squared jerk stayed within the comfortable range (≤1 m/s³) in every tested cell, including collisions, showing collision and comfort risk are governed by different parameters. Embedding a representative detection and elastic-control layer alongside headway optimization eliminated collisions within the tested range and remained robust at three times that severity, where headway alone failed; because the detector’s residual is computed directly from the true offset magnitude and detector failure is not modeled, this joint-defense result is illustrative rather than a validated-detector-calibrated estimate. These results give a reproducible, quantified basis for headway- and detection-based mitigation policy in connected-vehicle platoons. Full article

With increasing renewable and power-electronic penetration, emergency control must convert early post-fault measurements into feasible actions within a short latency budget. This paper proposes a response-driven online framework that uses the simplified branch transient transmission capacity (sBTTC) as a physically interpretable interface between causal stability forecasting, action-response prediction, and constrained control. A preceding masked Informer forecasts the no-control all-branch sBTTC trajectories from the first 1.00 s of measured response; a ConvLSTM then predicts generator-tripping recovery and the recovery associated with four load-shedding levels. These predictions are embedded in a weighted mixed-integer piecewise-linear model with stability-recovery, action-bound, and power-balance constraints. On the studied 100-bus renewable-rich AC/DC system, ConvLSTM achieved an RMSE of $7.193\times {10}^{-3}$ and an MAE of $5.674\times {10}^{-3}$ with 69.16 ms inference time. Its inference was 66.42% faster than Informer, while its RMSE was only 2.06% higher; relative to conventional LSTM, its RMSE and MAE were reduced by 28.21% and 21.53%, respectively. Across 62 grouped out-of-sample disturbances, the validation results give a 96.77% control success rate. In the representative disturbance, 900 MW of generation tripping and 740 MW of load shedding restored the nonlinear terminal sBTTC to 0.998, and the command was issued 1.36 s after fault inception. The framework provides an auditable forecast–response–decision chain; its additive approximation is restricted to the validated action range and uses an empirical 0.05 sBTTC recovery margin selected to exceed the observed 95th-percentile absolute error; this margin is not interpreted as a worst-case error bound. Full article

Reliable operating-state recognition of gas pressure regulators is essential for pressure stability, operational safety, and supply continuity in urban natural gas distribution networks. However, SCADA pressure–flow signals from regulating stations are often affected by non-stationary noise, impulsive disturbances, limited fault-state samples, and short-window temporal fluctuations, which reduce the reliability of data-driven recognition. To address these issues, this study proposes K²-TLNet, a noise-state-guided fault-state recognition framework for gas pressure regulation processes. The framework integrates adaptive Kalman filtering, training-only KMeans-SMOTE, parallel temporal convolutional network–long short-term memory feature extraction, and a Noise-Aware Gated Fusion mechanism. Adaptive Kalman filtering is used to generate denoised pressure–flow sequences and extract innovation-residual-based noise descriptors. These descriptors guide the fusion module to adaptively balance local transient features from the temporal convolutional network and contextual temporal features from long short-term memory. A field-SCADA-background-based semi-synthetic dataset was constructed using real operating records and mechanism-informed fault-state emulation rules. Experimental results demonstrate that K²-TLNet achieves 98.50% accuracy and 98.20% Macro-F1, while maintaining strong robustness under Gaussian and impulsive noise disturbances. Full article

The growing share of photovoltaic generation in power grids intensifies the need for converter architectures capable of combining efficient energy conversion, DC-bus stability, and ancillary service provision at the grid coupling point. This paper presents the modeling, implementation, and simulation-based evaluation of a 91 kWp three-phase photovoltaic (PV) system integrated with a battery energy storage system (BESS), developed in the PLECS environment. The proposed architecture comprises three interleaved Boost stages for maximum power point tracking (MPPT), a DC bus regulated at 600 V, three independent bidirectional buck–boost converters for LiFePO₄ bank management, and a two-level three-phase voltage source inverter (VSI) with an LC output filter. The control is organized in cascade voltage–current loops for the DC–DC stages and in vector control within the synchronous reference frame (SRF) for the inverter, with synchronization via SRF-PLL. A C-Script supervisory block integrates the Perturb and Observe (P&O) MPPT algorithm, independent state of charge (SOC) estimation per bank via coulomb counting, and Volt–VAR reactive power reference generation with a dead band of 0.90–1.10 pu. Five scenarios are analyzed for validation: DC-bus regulation under irradiance transients; reactive power support during undervoltage and overvoltage events (0.80–0.85 pu and 1.15–1.20 pu); BESS operation as an active DC-link support element; and PV curtailment with fully charged banks. All five scenarios were additionally corroborated on a Typhoon HIL402 Pro 2 hardware-in-the-loop platform, reproducing the PLECS waveforms within the amplitude and timing resolution of the oscilloscope captures. Across all scenarios, the DC bus is held within $\pm 15$ V (2.5%) of the 600 V reference, with the worst-case transient recovering in 80–100 ms; under a sustained 9 s bidirectional disturbance, redirecting PV surplus to BESS charging in both the undervoltage and overvoltage segments—with no externally imposed active-current limit—keeps the current-vector magnitude $\sqrt{i_d^2+i_q^2}$ below the 335 A rating throughout (≈271 A and ≈242 A, respectively), while the available reactive margin $Q_{disp}$ reaches ≈78–80 kVAr in both segments and the bank SOC advances by ≈$0.03$ pu; and supervisory curtailment under a sustained overvoltage ride-through with a saturated bank keeps the per-bank SOC dispersion within $4\times {10}^{-5}$ pu while expanding the available reactive margin $Q_{disp}$ from ≈50 to ≈90 kVAr. Full article

Grid-following (GFL) renewable energy stations may experience phase-locked loop (PLL)-dominated small-disturbance synchronization instability in weak grids, while grid-forming (GFM) devices can improve the damping of this mode. However, most current studies directly approximate GFM as an ideal voltage source without providing rigorous proof. There is also a lack of in-depth analysis on how the parameters of GFM affect its enhancement effect on the small disturbance synchronization stability of GFL. To address this gap, this paper establishes an ordinary differential equation model of the GFL/GFM hybrid system and proposes a fourth-order polynomial approximate root method suitable for polynomials with two pairs of weakly damped conjugate complex roots. Based on this method, the approximated form of the PLL damping is given, and the effect of the inertia time constant, damping coefficient, and capacity of a virtual synchronous generator (VSG) on the PLL mode damping was analyzed analytically. Moreover, it was proven that VSG with a certain level of inertia can play a role close to the ideal voltage source in improving the small disturbance synchronization stability of GFL. Finally, an electromagnetic transient simulation model was established on MATLAB/Simulink, and these conclusions were verified. Full article

To address the transient power surges and DC-link voltage fluctuations arising from fast frequency response demands in new power systems, this paper proposes a Natural Switching Surface (NSS) control strategy for active neutral-point clamped (ANPC) converters. First, the operating modes and working principles of the ANPC converter are analyzed, and the phase trajectory relationship between the inductor current and DC-side voltage under diverse operating conditions is mathematically derived. On this basis, a systematic NSS control law is established according to the piecewise mathematical model of the converter. Furthermore, a current-limited NSS control scheme is developed to suppress transient current spikes, which realizes smooth voltage and current output regulation and effectively mitigates power transients and DC voltage fluctuations induced by fast frequency response operations and external power disturbances. Comprehensive simulation and prototype experimental results validate the superior performance of the proposed method. Quantitative comparisons demonstrate that, compared with the conventional PI control, the proposed strategy shortens the converter startup time by 1.5 s, restricts the DC voltage drop within 15 V under power disturbance conditions (in contrast to over 60 V with PI control), and achieves faster dynamic recovery and higher operation stability. The proposed method provides an effective solution for high-performance fast frequency response and stable grid integration of renewable energy and energy storage systems. Full article

To improve the transient operating stability of Francis turbines under flexible regulation conditions, this study investigates the effects of different speed-change modes on the internal flow structure and pressure pulsation characteristics of a high-head Francis-99 model turbine during variable-speed transients. Three representative acceleration strategies, namely linear, quartic, and fourth-root speed-change modes, are designed. In all cases, the rotational speed increases from 333 r/min to 346.2 r/min within 4 s, corresponding to a speed increase of approximately 3.96%, thereby eliminating the influence of differences in speed-change amplitude and duration on the flow response. During this process, the main frequency induced by runner blade passing at the guide vane outlet increases from approximately 166.5 Hz to 173.1 Hz, while the main frequency induced by guide vane passing at the runner inlet increases from approximately 155.4 Hz to 161.6 Hz. Comparative analyses of the pressure distribution in the runner and guide vane regions, runner streamline evolution, time-domain pressure pulsation, and time–frequency characteristics obtained using the Hilbert–Huang transform show that the temporal distribution of the speed-change rate significantly affects pressure-field uniformity, flow-separation development, and spectral-energy distribution. The linear speed-change mode produces a continuous and relatively predictable migration of pressure and frequency. The quartic mode, characterized by a “slow-first and fast-later” strategy, delays the development of initial disturbances, yields a more balanced pressure-gradient distribution and more localized flow separation, and produces a more concentrated time–frequency energy distribution with shorter-lasting high-frequency pulsation regions. By contrast, the fourth-root mode induces excessive initial acceleration, leading to a polarized pressure distribution with high pressure at the inlet and low pressure at the outlet, large-scale separation vortices, persistent low-frequency modes, and nonlinear frequency coupling. The results indicate that, while satisfying rapid power-response requirements, avoiding excessive acceleration at the initial stage and adopting nonlinear acceleration strategies with an initial-buffering feature are effective approaches for improving the stability of variable-speed turbine transients. Full article

This paper proposes a phase-compensated enhanced second-order generalized integrator phase-locked loop (ESOGI-PLL) to suppress the frequency coupling effect (FCE) and its associated power quality degradation in grid-following inverters (GFLIs). An output impedance model incorporating FCE dynamics is formulated via signal perturbation analysis to quantify grid-current harmonic amplification and weak-grid instability boundaries. To suppress the FCE, the proposed ESOGI-PLL structurally embeds a phase-lead compensator, directly neutralizing the inherent phase lag of conventional filters. Simulation results demonstrate that the proposed ESOGI-PLL effectively mitigates PLL-induced frequency coupling, thereby improving the output-current quality and stability of GFLIs under weak-grid conditions. Compared with the synchronous reference frame phase-locked loop (SRF-PLL), the total harmonic distortion (THD) of the grid-current decreases from 24.33% to 2.47% under harmonic disturbances, while the transient settling time is significantly reduced, confirming the effectiveness of the proposed approach in enhancing both dynamic performance and output-current quality. Full article

An Adaptive-Parameter Maximum Correntropy Kalman Filter (APMCKF) algorithm is proposed to address state estimation degradation in semi-active suspensions caused by non-linear coupling between time-varying physical parameters and non-Gaussian noise. First, a time-varying dynamic model with non-linear damping is established via bench tests. A genetic algorithm (GA) globally optimizes key physical parameters to suppress model mismatch. Second, the APMCKF integrates an adaptive suspension parameter update mechanism. This closed-loop mechanism refreshes the system state matrix in real-time, effectively overcoming state-tracking lag. Concurrently, the maximum correntropy criterion (MCC) is embedded within the Sage–Husa recursive framework to dynamically reconstruct the observation noise covariance matrix, ensuring robust filtering under heavy-tailed noise. Simulations under ISO Class A–D random road profiles demonstrate that the APMCKF reduces the root-mean-square error (RMSE) by 62.33–81.24% compared to the adaptive Kalman filter (AKF). It also outperforms the adaptive-parameter Kalman filter (APKF), yielding a 27.49% accuracy improvement on Class D roads where non-Gaussian noise is most severe. Moreover, comparative evaluations against standard non-linear Bayesian filters demonstrate that the APMCKF successfully overcomes the truncation errors of the Extended Kalman Filter (EKF) and the tracking hysteresis of the Unscented Kalman Filter (UKF), reducing the average RMSE by up to 74.98% and 60.76%, respectively, under severe Class D non-Gaussian excitations. Furthermore, the algorithm exhibits excellent disturbance rejection under transient speed bump impacts and maintains stable error reduction across vehicle speeds of 10–25 m/s. Ultimately, the APMCKF delivers high-precision estimation and exceptional robust stability under variable speeds and non-Gaussian disturbances. Full article

The increasing integration of power electronic converters in hybrid AC/DC microgrids introduces significant challenges in maintaining DC-link voltage stability during mode transitions, where uncoordinated actions cause large voltage deviations. This paper proposes a coordinated hierarchical control strategy incorporating a supervisory finite state machine (FSM) and a slew-rate-limited reference shaping mechanism to ensure smooth transitions in a microgrid interfaced through a bidirectional DC–DC converter and a three-level T-type inverter. The supervisory layer coordinates the sequencing of subsystem activation and routes all mode changes through a dedicated transition state in which the power reference is gradually shaped to suppress DC-link disturbances, while a dedicated resynchronization state manages reconnection to the grid after a sustained outage. The strategy is validated through detailed switching-level simulations across five operating scenarios, including islanded load energization, grid blackout, discharging-to-charging transitions, state-of-charge limit management, and grid restoration through reclosing and resynchronization, and is further compared against a droop-based coordination scheme. Simulation results demonstrate that the proposed approach reduces the transient DC-link voltage deviation from approximately 18–20% to below 7%, and to as low as 2.6%, without introducing steady-state error, confirming its effectiveness in enhancing the dynamic stability of the system during mode transitions. Full article

Asynchronous motors are widely used in electric vehicle drive systems because of their simple structure, low cost, and high reliability. Accurate speed tracking and smooth transient response are important during start-up, acceleration, and deceleration. However, sensing uncertainties and sensor faults may affect the measured signals and reduce control performance. In this study, an adaptive prescribed performance control (PPC) method is developed for asynchronous motor speed regulation. A nonlinear mapping and an improved tangent-type barrier Lyapunov function (BLF) are used to remove the requirement that the initial tracking error must lie within the prescribed performance bounds. Radial basis function neural networks are used to approximate the unknown nonlinear terms. The stability analysis shows that all closed-loop signals remain bounded and that the tracking error enters and remains within the prescribed performance region after the initial expansion stage. Simulations under different initial motor speeds, the considered sensor-fault conditions, and load disturbances are conducted. Under the adopted comparative conditions, the proposed method reduces the convergence time, steady-state error, maximum tracking error, and recovery time by 69.5%, 93.4%, 92.2%, and 49.4%, respectively. The results show that the proposed method improves the transient response, tracking accuracy, and disturbance recovery of the asynchronous motor drive system. Full article

With the increasing integration of large-scale renewable energy sources (RESs), modern power grids are evolving into low-inertia and weak-damping networks, creating challenges for transient power-angle stability. Conventional grid-following (GFL) control strategies present a lagging synchronization response under weak grid conditions due to their reliance on phase-locked loops (PLLs). Although grid-forming (GFM) control via virtual synchronous generators (VSGs) provides standalone voltage source properties, conventional fixed-parameter VSGs exhibit an inherent design trade-off between first-swing angular suppression and post-fault oscillation damping during severe short-circuit disturbances. To resolve these vulnerabilities, this paper proposes an adaptive VSG control strategy designed to improve the transient power-angle response of the investigated system. By establishing a parametric judgment framework based on real-time frequency deviations and acceleration rates, the virtual inertia $J\left(t\right)$ and damping coefficient $D\left(t\right)$ are adaptively adjusted within predefined limits. Furthermore, a current-limiting mechanism is incorporated into the parameter adaptation loops to prevent converter overcurrent tripping. To evaluate the proposed method, an aggregated grid-connected benchmark system comprising a 5 MVA PMSG-based wind farm, a conventional synchronous generator, and an external grid is implemented in MATLAB/Simulink. The simulation results under continuous ambient operational fluctuations and severe three-phase short-circuit faults demonstrate that the proposed strategy reduces the first-swing power-angle peak by approximately 31% compared with the conventional fixed-parameter VSG, and the response settles within approximately 0.4 s in the investigated fault case. These results indicate the simulation-based feasibility of the proposed bounded adaptive strategy. Further real-time, hardware-in-the-loop, and experimental validation is required before practical implementation. Full article

In response to the severe chattering, slow dynamic response, and limited disturbance rejection capability of switched reluctance motor (SRM) drive systems under conventional control methods, this paper develops an improved nonsingular fast terminal sliding mode controller (INFTSMC). An integral sliding surface is first designed to eliminate the steady-state tracking error. An adaptive exponent and an improved double-power reaching law are then introduced to enhance the convergence performance. In addition, a smooth hyperbolic tangent approximation and a boundary layer design are employed instead of the conventional signum function to suppress chattering while maintaining a rapid response. Theoretical analysis demonstrates that the sliding variable is globally asymptotically stable and enters any prescribed neighborhood of the origin within a fixed time independent of the initial condition, thereby establishing practical fixed-time convergence rather than exact finite-time stability. Furthermore, an error-dependent bandwidth scheduling mechanism is incorporated into the modified super-twisting observer, resulting in an adaptive bandwidth modified super-twisting observer (AB-MSTO) for load torque estimation and compensation. The proposed bandwidth scheduling mechanism improves the balance between transient estimation speed and steady-state noise sensitivity. Finally, a MATLAB/Simulink simulation platform is constructed to evaluate the proposed control strategy. The simulation results demonstrate that the proposed INFTSMC combined with the AB-MSTO improves the dynamic speed regulation performance and disturbance rejection capability of the SRM drive system under different operating conditions. Full article