Search Results (2,872)

To address the issues of slow response to preceding vehicles and poor string stability in distributed platoon control of connected and autonomous vehicles (CAVs) under mixed traffic flow, this paper proposes a sliding mode control method based on LSTM trajectory prediction, denoted as LSTM-SMC, within a multi-agent framework. The LSTM model is trained using the HighD naturalistic driving dataset to achieve high-precision prediction of the leader vehicle’s trajectory over a horizon of 3 s, with root mean square errors (RMSE) of 8.52 m in the X-direction and 0.896 m in the Y-direction. The predicted trajectory information is converted into a preview error and embedded directly into the design of the sliding surface, enabling each following vehicle to anticipate disturbances before they propagate. A diminishing preview gain strategy (${\gamma }_1=0.4$, ${\gamma }_2=0.2$, ${\gamma }_3=0.1$) is employed to suppress error propagation along the platoon, while a saturation function is introduced to eliminate chattering and ensure smooth control inputs. Three simulation scenarios—prescribed leading, HDV (human-driven vehicle) leading, and curved road scenario—are constructed to validate the proposed method against traditional constant time headway (CTH) control, pure sliding mode control (SMC), and LSTM-MPC. Results demonstrate that under extreme conditions, the proposed method reduces the speed RMSE of the 3rd following vehicle by 18.3% compared to CTH and by 39.7% compared to SMC. Under HDV leading conditions, all string stability amplification factors are less than 1, and the position RMSE of the 3rd vehicle is only 5.03 m in the curved road scenario. Compared with LSTM-MPC, the proposed LSTM-SMC achieves comparable tracking accuracy while reducing computational cost by 1.43–3.51×. The proposed method achieves a native integration of prediction and robust control, significantly improving tracking accuracy, string stability, and computational efficiency across diverse operating conditions in mixed traffic flow. Full article

Electric Vehicle drive systems must provide fast torque response, low or minimal torque ripple, robustness to both parameter variations and external disturbances. Permanent Magnet Synchronous Motors (PMSMs) are commonly found in electric vehicle propulsion applications due to their high power density, high efficiency, and excellent dynamic performance. However, performance degradation in torque control of PMSMs under time-varying conditions arises from the nonlinear characteristics of motors and their high sensitivity to changes in system parameters. This paper presents a torque-control method with high dynamic bandwidth that combines three techniques: (1) Nonlinear Sliding Mode Torque Control; (2) Predictive Current Control; and (3) Disturbance Estimation. The sliding mode controller provides improved robustness against uncertainties about the system. In addition, the predictive current control provides improved accuracy in current tracking and significantly reduces the time required to achieve a steady state. A disturbance observer is used to compensate for load disturbances and model errors in the motor model. The integrated control architecture is simulated and modeled in MATLAB/Simulink for a typical EV driving environment. The simulation framework produced faster and more accurate torque tracking than conventional PI-type vector controllers, as well as reduced torque ripple and improved disturbance rejection under similar operating conditions. The results demonstrate that the proposed method is a viable candidate for high-performance EV propulsion systems while acknowledging practical limitations such as chattering, tuning complexity, sampling time sensitivity, and the need for further experimental validation. Full article

The development of fractional-order control has been derived from the mathematical generalization of classical calculus and has become an important tool in the modeling and control of dynamical systems with memory and hereditary effects. In spite of the rapid development of this area of control theory and applications, the overall scientific development, structure, and engineering relevance of fractional-order control remain insufficiently understood. In this paper, we address this problem by combining large-scale bibliometric analysis with representative controller performance studies. A total of 6482 publications indexed in the Web of Science database during the period 2010–2026 are analyzed. The bibliometric results indicate that fractional-order control is an increasingly connected global research field with strong roots in fractional calculus, advanced control theory, and growing interdisciplinary links with applied mathematics, automation, and computer science. To further illustrate controller level behavior, representative simulations are performed on a fractional-order time-delay process and an uncertain nonlinear system. For the fractional-order time-delay process, a well-tuned PID controller is compared with a realizable FOPID controller implemented through Oustaloup recursive approximation. The results show that the FOPID controller improves several performance measures, including overshoot, settling time, control energy, total variation, and sensitivity peak, while the comparison is interpreted as a performance trade-off rather than universal superiority. For the uncertain nonlinear system, fractional-order sliding mode control produces smoother control action and substantially reduces chattering. By combining bibliometric mapping with representative performance evaluation, this paper provides a comprehensive overview of fractional-order control as a globally active and practically relevant discipline in control engineering. Full article

Wireless power transfer (WPT) systems are easily affected by input voltage variation, coupling variation, and load changes, resulting in output voltage fluctuation and long settling time. To improve the transient performance, this article proposes a discrete sliding mode control method with lumped disturbance estimation (LDE-DSMC) for an LCC–S compensated WPT system. Input voltage variation, mutual inductance variation, load step, and unmodeled dynamics are uniformly treated as a lumped disturbance in the output voltage channel. The estimated disturbance is introduced into the control law for feedforward compensation, and one-step prediction is used to reduce the influence of duty cycle update delay. A hardware prototype is built for verification. Compared with PI control and adaptive feedforward control, the proposed method achieves smaller output voltage deviation and shorter settling time under different disturbances. In the single disturbance tests, the maximum output voltage deviation is reduced by at least 50%, and the settling time is shortened by at least 33%. Under the compound disturbance, the maximum output voltage deviation is reduced by 62.50% and 36.36% compared with PI control and adaptive feedforward control, respectively, while the settling time is shortened by 64.49% and 39.68%. Full article

This paper investigates the fault-tolerant constrained control problem of a nonlinear quarter-car active suspension system subject to road disturbances, body-state constraints, and mixed actuator faults. When mixed actuator faults, state constraints, unknown nonlinear suspension dynamics, and convergence-time requirements coexist, it remains challenging to simultaneously guarantee fault-tolerant compensation, constraint preservation, and implementable control laws. To address these challenges, a neural-network control method based on an adaptive prescribed-time filter (APF) is proposed. A logarithmic state transformation is introduced to convert the body-displacement and velocity constraints into boundedness problems of transformed variables, and the sprung-mass subsystem is represented in a strict-feedback form. The unknown nonlinearities induced by suspension dynamics, road disturbances, and additive actuator faults are approximated online by radial basis function neural networks. Meanwhile, the APF is employed to avoid repeated differentiation of virtual control laws in backstepping and to achieve practical prescribed-time stability. Lyapunov analysis proves that all closed-loop signals are bounded, the body-state constraints are preserved, and sufficient conditions are obtained for the boundedness of the unsprung-mass dynamics, as well as the safety of suspension travel and tire dynamic load. Simulation results under sinusoidal road excitation and smooth-transition actuator faults show that, compared with PID control, passive suspension, and sliding mode control, the proposed method reduces the body-displacement RMSE by 77.39%, 91.83%, and 73.12%, respectively, and the RMS body acceleration by 70.34%, 87.73%, and 50.22%, respectively, while maintaining suspension travel and tire dynamic load within their safety bounds. Full article

The increasing demand for clean, reliable, and sustainable energy has intensified the need for advanced control strategies in modern wind energy conversion systems. Although conventional backstepping control (BC) offers strong stability and robustness, its performance may deteriorate under parameter uncertainties and dynamic operating conditions, leading to power fluctuations and reduced energy quality. To overcome these challenges, this study proposes an intelligent fuzzy fractional-order BC (FFOBC) strategy for multi-machine wind energy systems. By integrating fuzzy logic with fractional-order calculus into the classical BC framework, the proposed approach enhances adaptability, dynamic response, and robustness against system disturbances and nonlinearities. The controller is implemented at the machine-side inverter and validated in MATLAB/Simulink under varying wind and load conditions. Comparative results demonstrate that the proposed FFOBC significantly outperforms conventional sliding mode control in terms of overshoot reduction, steady-state accuracy, response smoothness, and total harmonic distortion minimization. Furthermore, the proposed strategy improves energy conversion efficiency, reduces mechanical and electrical stress, and ensures stable power injection into the grid. These findings highlight the potential of the proposed intelligent control framework to support sustainable, resilient, and high-quality wind energy integration in future smart power systems. Full article

Sliding mode control (SMC) has emerged as a robust and adaptive strategy for grid-tied inverters. It has unique attributes which make it an appropriate control choice under increasingly complex power systems. However, there are a limited number of review articles which comprehensively explore the true potential of SMC for grid-tied inverter applications. This systematic review has been structured to explore SMC techniques with respect to certain challenges, i.e., stability challenges, unbalanced conditions, low inertia scenarios, and harmonics distortion. The classification of various SMC techniques is presented with respect to their control law and sliding surfaces design. The comparative analysis indicates the dominance of artificial intelligence (AI)-assisted control systems, which represent a paradigm shift in modern-era control systems. Key performance matrices, i.e., total harmonics distortion (THD) reduction, tracking accuracy, and response time, etc. are compared across various SMC techniques. Moreover, this review identifies possible research gaps regarding the conceptual integration of quantum computing with SMC. Furthermore, several future directions are presented in this article to make SMC more robust and reliable for the next generation of AI-dominated grid-tied inverter applications. Full article

To achieve manipulator trajectory tracking under uncertainties and external disturbances, this study develops a prescribed performance nonsingular sliding mode control strategy. A new sufficient condition for predefined-time stability is established and proved. A predefined-time nonlinear disturbance observer is designed to estimate the lumped disturbance, and a prescribed performance function is introduced to confine the tracking error within predefined bounds. A predefined-time nonsingular sliding mode surface is constructed, while a saturation function and a hyperbolic tangent function are adopted to address singularity and chattering, respectively. Numerical simulations are conducted on a two-degree-of-freedom manipulator subject to 20% parametric uncertainties and time-varying external disturbances. The effectiveness of disturbance compensation is evaluated by comparing the control performance with and without observer compensation, and the proposed method is further compared with fixed-time and finite-time sliding mode controllers. Quantitative results show that, with observer compensation, the integral absolute error (IAE), integral squared error (ISE), and root mean square error (RMSE) are reduced by 71.63%, 12.95%, and 6.60% for Joint 1, and by 79.24%, 35.57%, and 19.55% for Joint 2, respectively. Moreover, compared with the fixed-time method, the proposed controller reduces the IAE by 54.3% for Joint 1 and 63.1% for Joint 2, while the corresponding reductions relative to the finite-time method are 89.0% and 93.3%, respectively. These results verify the effectiveness of the proposed scheme in disturbance rejection and tracking accuracy. Full article

Reliable indoor localization is required for automated guided vehicles (AGVs), robot validation, and industrial digital-twin applications, but ultrasonic positioning can degrade sharply when acoustic visibility changes. This paper evaluates Marvelmind Super-Beacon localization in controlled laboratory experiments involving both AGV tracking and UR10 robot-arm positioning. The non-inverse architecture (NIA) and inverse architecture (IA) configurations are included as parallel validation scenarios to assess the robustness of the proposed mitigation framework across different Marvelmind deployment modes. The baseline analysis identifies the dominant acoustic failure modes, including multipath-induced scatter, crossover-zone handover jumps, update-rate degradation, complete non-line-of-sight (NLoS) outages, and height-dependent 3D jitter. To mitigate these effects, an embedded ultrasonic–inertial pipeline is implemented on an ESP32-S3-WROOM-1 module. The system combines UART packet validation, interrupt-driven ICM-20948 inertial acquisition at 500 Hz, sliding-window kinematic outlier rejection, and a 15-state error-state Kalman filter (ESKF). The embedded estimator logic is designed to maintain motion continuity during intermittent or corrupted acoustic positioning while reintroducing validated ultrasonic absolute corrections. Using recorded AGV and UR10 datasets, mitigation performance was quantitatively assessed through a firmware-consistent replay of the recorded measurements, using the same gating, inertial propagation, and measurement-update logic as the real-time ESP32-S3 implementation. Across ten trials per configuration, the replay-based trial-mean RMSE in the 2D AGV scenarios decreased from 101.2–104.1 mm for raw ultrasonic data to 47.2–48.7 mm after fusion, while peak failure-interval errors were reduced by 64.2–65.7%. In the 3D UR10 scenarios, replay-based trial-mean RMSE decreased from 157.6–158.4 mm to 80.2–80.5 mm, and peak height-sensitive 3D errors were reduced by 58.8–60.0%. The results demonstrate the feasibility of embedded ultrasonic–inertial robustness enhancement for localization in controlled laboratory AGV and robot-arm scenarios. While the proposed approach shows promising performance under the investigated conditions, further validation is required before extending the conclusions to larger-scale and dynamically changing industrial environments. Full closed-loop online robot localization and control based directly on the fused localization output remain subjects for future investigation. Full article

To address the robustness limitations of three-vector model predictive current control (TV-MPCC) in permanent magnet synchronous motor (PMSM) drives under parameter variations and external disturbances, this paper proposes an improved sliding mode observer (SMO) based on a novel dual power-rate reaching law combined with a hyperbolic tangent function (PTHSMO) for back-EMF estimation and feedforward compensation. The proposed reaching law integrates a terminal attractor term and a nonlinear power-rate term to achieve fast convergence, while the tanh-based switching term continuously approximates the sign function to suppress chattering without requiring a downstream low-pass filter. The estimated back-EMF, which encapsulates the combined effect of parameter mismatch and actual back-EMF, is fed forward into the TV-MPCC prediction model to actively compensate for residual disturbances (denoted PTHESMO). The stability of the observer is verified via the Lyapunov method. Compared with the traditional SMO-based TV-MPCC, the proposed method reduces startup overshoot by approximately 46%, decreases speed recovery time under a 0.3 Nm load disturbance from 46.2 ms to 24.5 ms, and reduces rotor position error from 0.1358 rad to 0.1266 rad, providing an effective solution for high-performance sensorless PMSM drive control. Full article

Maintaining precise liquid levels in interconnected tank systems is a critical requirement in many industrial processes; however, achieving reliable control remains challenging due to inherent nonlinearities and external disturbances. This paper presents a comparative analysis of three control strategies—sliding mode control (SMC), feedback linearization (FL), and proportional–integral–derivative (PID) control—applied to a nonlinear two-tank system. To address the practical limitation of unmeasured system states, a high-gain observer (HGO) is integrated into the control architecture to reconstruct unmeasured water levels. In addition, the controller and observer parameters are optimized using a hybrid genetic algorithm to balance tracking precision and control effort. Simulation results demonstrate that, although all three methods achieve acceptable setpoint tracking performance, the SMC-HGO configuration exhibits superior robustness. Specifically, it outperforms FL and PID in rejecting external disturbances and maintaining stability under significant parameter variations, such as changes in discharge coefficients. Full article

Four-wheel independent steering (4WIS) vehicles can improve low-speed maneuverability and high-speed stability by independently regulating the steering angles of all four wheels. However, under large-curvature trajectories, parameter perturbations, and external disturbances, inconsistent coordination among the four-wheel steering angles may increase tire lateral slip, yaw response deviation, and trajectory tracking errors. To address the difficulty of conventional trajectory tracking methods in simultaneously ensuring geometric consistency, tracking accuracy, and robustness, this paper proposes an adaptive sliding mode trajectory tracking control method based on instantaneous center of rotation (ICR) constraints. First, the tire instantaneous turning center (TTC) of each wheel is derived using rigid-body spatial kinematics, and the TTCs are mapped onto a unified vehicle-body reference plane based on the SAE J670 coordinate system to obtain a real-time vehicle-level ICR estimation. Second, a lateral–yaw dynamic model and a trajectory tracking error model are established. The yaw rate and sideslip angle are corrected using ICR geometric information, and an adaptive sliding mode controller is designed with an equivalent control term, adaptive switching gain, adaptive boundary layer, and sideslip suppression term. The uniform ultimate boundedness of the sliding variable and closed-loop tracking errors is proven using Lyapunov theory. Finally, MATLAB (2023a)2024/CarSim (2019) co-simulations are conducted under small-curvature sinusoidal, double-lane-change, large-curvature sinusoidal, low-adhesion, and mass-perturbation conditions. The results show that the proposed ICR-SMC method significantly reduces lateral and heading errors compared with U-LQR and U-SMC, especially under large-curvature and low-adhesion conditions, demonstrating improved tracking accuracy and robustness for 4WIS vehicles. Full article

For the trajectory tracking control problem of a 7-DOF redundant hydraulic manipulator, an adaptive fuzzy sliding mode control method based on a novel fast reaching law is proposed. Based on the kinematic analysis of the manipulator, its dynamic equation is constructed using the Lagrange dynamic equation. A trajectory planning method for the manipulator, integrating seventh-order polynomial interpolation and genetic algorithm optimization, is proposed. Taking the planned trajectory as the expected trajectory, a sliding mode controller is designed to achieve trajectory tracking control of the manipulator. A sliding mode disturbance observer is used to observe the system uncertainties, and an adaptive fuzzy logic system is designed to estimate the observation error of the disturbance observer. The sliding mode control law is deduced based on the fast reaching law, which can achieve global fast convergence of the sliding mode function while reducing the chattering of the controller. The simulation results show that the proposed control method has good tracking performance and strong robustness. Full article

This paper proposes an integrated attitude control framework for flexible spacecraft subject to external disturbances, rigid–flexible dynamic coupling, and actuator faults. The control framework combines the Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithm with an adaptive fault-tolerant (AFT) compensator. First, a rigid–flexible coupling dynamic model is formulated using Modified Rodrigues Parameters. Second, an observer-based TD3 attitude controller is designed, where a hierarchical reward function incorporating the observer-estimated flexible modal displacement $\widehat{\mathit{\eta }}$ is constructed to train the agent for simultaneous attitude convergence and vibration suppression. Third, a composite fault-tolerant control structure is developed by integrating the trained TD3 policy with an adaptive sliding mode compensator that handles both partial loss-of-effectiveness faults and time-varying additive faults. The proposed framework is evaluated under a progressive five-scenario uncertainty evaluation framework encompassing measurement noise, parameter mismatch, external disturbances, and actuator faults. Simulation results demonstrate that (i) the $\widehat{\mathit{\eta }}$-augmented reward enables substantial improvements in vibration suppression over the baseline reward, achieving a better balance between pointing accuracy and vibration attenuation; (ii) under the most demanding fault scenario, the AFT compensator proves essential for precise convergence, and the composite TD3+AFT architecture achieves the best overall performance among the four compared control schemes. Full article

This paper proposes an integrated formation control framework with a finite-time nonlinear disturbance observer (FT-NDO) for automated guided vehicles (AGVs) operating in port environments, where constrained workspace, narrow formation spacing, and complex external disturbances pose significant challenges. An adaptive leader–follower formation strategy with dynamic inter-vehicle spacing is developed to enhance maneuverability during turning. Within a hierarchical control structure that decouples lateral and longitudinal dynamics, two sliding mode controllers (SMCs) are designed: (a) a lateral SMC that prioritizes heading accuracy, limiting yaw angle error to within ±2°; and (b) a nonsingular terminal SMC (NTSMC) for longitudinal control, improving error convergence speed compared to conventional SMC. An FT-NDO is further incorporated into both control loops to estimate and compensate for external disturbances in real time, achieving a disturbance estimation accuracy of over 95% and significantly attenuating the impact of environmental disturbances. Validation through simulation and physical experiment of a dual-AGV formation in a realistic port scenario demonstrates that the proposed approach restricts formation deviation to 0.015 m and maintains stable operation under various disturbance conditions. This study provides a practical solution for dual-AGV collaborative transportation in spatially constrained and dynamically disturbed environments, with direct implications for improving operational efficiency and safety in port logistics. Full article