Search Results (934)

This paper presents a composite control strategy for gearless coal mill to improve the disturbance immunity under low-speed variable operating conditions. First, the gearless coal mill encounters power supply voltage fluctuations, mechanical failures, or ambient temperature changes during operation. These situations can cause the system to suffer from the problem of insufficient control accuracy of the rotational speed. Therefore, a non-singular fast terminal sliding mode control strategy is proposed to improve the speed response. Then, to address the problem of load perturbation caused by different coal quality, this paper designs the extended state observer. Feed-forward compensation of the perturbation is performed to improve the robustness. Finally, due to the parameter mismatch problem caused by heat in operations that take a long time, this paper proposes a sliding-mode-based deadbeat predictive current control. The strategy possesses the fast dynamic response of deadbeat predictive current control while retaining the strong robustness of sliding mode control. Lyapunov proved the stability of the proposed control strategy. The experimental results verified that the proposed control strategy had better control performance. Full article

To suppress the bus voltage fluctuations caused by disturbances such as photovoltaic-side power fluctuations and load-side power variations in hybrid energy storage systems, a fixed-time active disturbance rejection controller (FxADRC) integrated with a cascaded extended state observer (CESO) is proposed in this paper. The paper first constructs a dynamic model of the hybrid energy storage system, considering the impact of disturbances. Second, this paper designs a cascaded extended state observer to estimate the total disturbances affecting the system, achieving finite-time convergence performance. Then, a fixed-time sliding mode active disturbance rejection control strategy combined with the CESO is proposed, which can achieve bus voltage tracking with fixed-time convergence rate irrespective of the effect of the initial state. In addition, the stability of the proposed controller is validated by the Lyapunov method. Finally, Comparative studies are conducted by simulation to verify the effectiveness and outstanding performance of the proposed control scheme. Full article

High-performance tracking control for the hydraulic manipulator should address the challenges of the uncertainties and unknowns associated with the electro-hydraulic servo system (EHSS). This paper presents an extended state observer-based chattering-free terminal sliding-mode (ESO-CFTSM) control scheme for hydraulic manipulators. A third-order integral chain model is developed to characterize the system dynamics, where uncertainties and unknowns are considered as disturbances and estimated by the ESO. Meanwhile, a full-order TSM manifold is designed to stabilize the closed-loop system in finite-time. For this proposed scheme, the feedforward compensation of disturbances is introduced in the equivalent control law. Furthermore, the composite reaching law and a low-pass filter are used to realize the chattering-free control. The singularity is avoided because there are no derivatives of terms with fractional powers in the control law. The stability of the overall system is proved by Lyapunov technique. The simulations using the physical model of a hydraulic manipulator with coupled dynamics show the effectiveness of the proposed scheme for trajectory tracking problems. Simulation results indicate that the proposed ESO-CFTSM can achieve superior performance without being affected by lumped disturbances. Full article

This paper presents a global fixed-time control framework to address the target circumnavigation tracking problem of underactuated unmanned surface vehicles (USV) under unknown velocity states, lumped uncertainties, and actuator saturation. At the core of this approach is a novel fixed-time target-enclosing line-of-sight (FTTELOS) guidance law, designed to generate the desired heading angle and surge velocity. To estimate unknown velocities, external disturbances, and unmeasured system states, a set of fixed-time observers is constructed, consisting of a velocity observer, a disturbance observer, and a high-dimensional extended state observer (HFTESO). Moreover, to enhance robustness and effectively tackle actuator saturation, the control scheme incorporates a fixed-time sliding mode controller, a dynamic auxiliary system, and a fixed-threshold event-triggered mechanism. Simulation results using SimuNPS demonstrate that the proposed method enables rapid and smooth target circumnavigation, with all system errors converging to an arbitrarily small neighborhood of the origin within a fixed time. Theoretical analysis and simulation studies confirm the effectiveness and robustness of both the FTTELOS guidance law and the integrated control strategy. Quantitatively, compared with the traditional target-enclosing line-of-sight (TELOS) method, the proposed FTTELOS reduces the convergence time of the distance error ${\delta }_e$ from 13.64 s to 10.22 s and the angular error ${\varphi }_e$ from 10.46 s to 7.52 s, demonstrating a significant improvement in convergence speed and overall control performance. Full article

This paper proposes a novel fixed-time super-twisting sliding mode control (ST-SMC) strategy for uncertain robotic arm systems, aiming to address the issues of control chattering and the uncontrollable upper bound of convergence time in traditional sliding mode control algorithms. The proposed approach enhances system robustness, suppresses chattering, and ensures that the convergence time of the robotic arm can be explicitly bounded. First, a sliding surface with fixed-time convergence characteristics is constructed to guarantee that the tracking errors on this surface converge to the origin within a prescribed time. Then, an immersion and invariance (I&I) disturbance observer with exponential convergence properties is designed to estimate large, time-varying disturbances in real time, thereby compensating for system uncertainties. Based on this observer, a new super-twisting sliding mode controller is developed to drive the trajectory tracking errors toward the sliding surface within fixed time, achieving global fixed-time convergence of the tracking errors. Simulation results demonstrate that, regardless of the initial conditions, the proposed controller ensures fixed-time convergence of the tracking errors, effectively eliminates control torque chattering, and achieves a tracking error accuracy as low as 2 × 10⁻⁹. These results validate the proposed method’s applicability and robustness for high-precision robotic systems. Full article

A sliding mode predictive control (SMPC) scheme integrated with an extreme learning machine (ELM) disturbance observer is proposed for the trajectory tracking of a flexible air-breathing hypersonic vehicle (FAHV). To streamline the controller design, the longitudinal model is decoupled into a velocity subsystem and an altitude subsystem. For the velocity subsystem, a proportional-integral sliding mode surface is designed, and the control law is derived by minimizing a cost function that weights the predicted sliding mode surface and the control input. For the altitude subsystem, a backstepping control framework is adopted, with the SMPC strategy embedded in each step. Multi-source disturbances are modeled as composite additive disturbances, and an ELM-based neural network observer is constructed for their real-time estimation and compensation, thereby enhancing system robustness. The semi-globally uniformly ultimately bounded (SGUUB) stability of the closed-loop system is rigorously proven using Lyapunov stability theory. Simulation results demonstrate the comprehensive superiority of the proposed method: it achieves reductions in Root Mean Square Error (RMSE) of 99.60% and 99.22% for velocity and altitude tracking, respectively, compared to Prescribed Performance Control with Backstepping Control (PPCBSC), and reductions of 98.48% and 97.12% relative to Terminal Sliding Mode Control (TSMC). Under parameter uncertainties, the developed ELM observer outperforms RBF-based observer and Extended State Observer (ESO) by significantly reducing tracking errors. These findings validate the high precision and strong robustness of the proposed approach. Full article

We present a photoacoustic spectroscopy (PAS)-based method using a laser Doppler vibrometer (LDV) for real-time detection of laser-induced damage (LID) in optical components. By measuring audible frequency surface vibrations, the method enables remote, non-contact, and sensitive detection. Experiments with various dielectric optics (slide glass and single-layer coatings) and pulse durations (7 ns and 360 ps) of an Nd:YAG laser (wavelength of 1064 nm) showed detection accuracy comparable to microscopy. Vibration spectra correlated with natural modes calculated by finite element modeling, and vibrations according to the detecting location were observed. The method remained effective under typical mounting conditions, demonstrating its practical applicability. This PAS-LDV approach offers a promising tool for in situ monitoring of LID in high-power laser systems. Full article

With the comprehensive digitalization and electrification of aircraft, electromechanical actuation systems (EAS) have been increasingly applied. However, EAS are affected by various nonlinear factors, such as friction and mechanical backlash, which can compromise system stability and control accuracy, thereby reducing the operational lifespan of the EAS. This study focuses on these two nonlinear factors and proposes a hybrid control approach to mitigate their effects. In the speed loop of the EAS, a Super-Twisting sliding mode controller combined with a generalized proportional–integral observer (GPIO) is designed, while in the position loop, a hybrid controller integrating a radial basis function (RBF) neural network with sliding mode control is implemented. Leveraging the advantages of numerical analysis in SIMULINK and dynamic simulation in ADAMS, a co-simulation framework is established to evaluate the hybrid control algorithm under nonlinear effects. Furthermore, a control test bench for the control surface transmission system is constructed to analyze the dynamic and static performance of the system under different control strategies and input commands. The experimental results show that, compared with the PID control, the hybrid control method reduces the steady-state error and vibration amplitude of the step response displacement by 51% and 75%, respectively, and decreases the amplitude of speed fluctuations by 75%. For the sinusoidal response, the displacement lag is reduced by 76%, and the amplitude of speed fluctuations is reduced by 50%. Full article

The increased penetration of power electronics interfaced resources in modern power systems is unlocking new opportunities and challenges. New concepts like multiport converters can further enhance the efficiency and power density of power electronics-based solutions. The triple active bridge is an isolated multiport converter with soft switching and high voltage gain that can integrate different sources, storage, and loads, or act as a building block for modular systems. However, the triple active bridge suffers from power flow cross-coupling, which affects its dynamic performance if it is not removed or mitigated. Unlike the extensive literature on two-port power converters, studies on modeling and control comparison for multiport converters are still lacking. Therefore, this paper presents and compares different modeling and decoupling control approaches applied to the triple active bridge converter, highlighting their benefits and limitations. The converter operation and modulation are introduced, and modeling and control strategies based on the single phase shift power flow control are detailed. The switching model, generalized full-order average model, and the reduced-order model derivations are presented thoroughly, and a comparison reveals that first harmonic approximations can be detrimental when modeling the triple active bridge. Furthermore, the model accuracy is highly sensitive to the operating point, showing that the generalized average model better represents some dynamics than the lossless reduced-order model. Furthermore, three decoupling control strategies are derived aiming to mitigate cross-coupling effects to ensure decoupled power flow and improve system stability. To assess their performance, the TAB converter is subjected to power and voltage disturbances and parameter uncertainty. A comprehensive comparison reveals that linear PI controllers with an inverse decoupling matrix can effectively control the TAB but exhibit large settling time and voltage deviations due to persistent cross-coupling. Furthermore, the decoupling matrix is highly sensitive to inaccuracies in the converter’s model parameters. In contrast, linear active disturbance rejection control and sliding mode control based on a linear extended state observer achieve rapid stabilization, demonstrating strong decoupling capability under disturbances. Furthermore, both control strategies demonstrate robust performance under parameter uncertainty. Full article

This paper presents a Prescribed Performance Control (PPC) approach for robotic systems experiencing communication delay and disturbances. Under input and feedback delays, a state feedback controller is designed to maintain the output tracking error within prescribed performance specifications. Additionally, a super-twisting algorithm-based sliding-mode observer is proposed to estimate and compensate for external disturbance in the robotic system. Based on the Lyapunov method, appropriate controller parameters and observer gains are selected to ensure the accuracy of output tracking and disturbance estimation. Finally, the effectiveness of the proposed approach is validated through simulations on a nonlinear robotic system. The proposed method remains effective in the simultaneous presence of state measurement delay, control input delay, and disturbance. Full article

This paper presents a new robust control strategy for buck DC–DC converters that achieve fast and robust voltage regulation in the presence of load disturbances and model uncertainties. First, an adaptive state observer is designed to estimate the inductor current and capacitor voltage by utilizing the output measurement. The observer gains are tuned online via a Lyapunov-based adaptation law, ensuring that the estimation error remains uniformly bounded, even when the disturbances act on the system. Based on the state estimates, an integral sliding-mode controller is designed in order to eliminate the steady state error and ensure the finite time sliding. The detailed stability proofs for both the observer and the sliding-mode controller are derived showing the finite-time reaching of the sliding surface and exponential convergence of the voltage error. Simulation results under varying load profiles confirm that the proposed scheme outperforms traditional sliding-mode designs in terms of disturbance rejection and settling time, while avoiding excessive chattering. Full article

In this paper, a hybrid fault-tolerant control (FTC) system for quadcopter unmanned aerial vehicles (UAVs) is proposed to counteract the deterioration of the performance of the quadcopter due to motor faults. A robust and adaptive approach to controlling fault conditions is simulated by combining an integral back-stepping controller for translational motion and a nonlinear observer-based sliding-mode controller for rotational motion, and then implemented on an FPGA. Finally, motor faults are treated as disturbances and are successfully compensated by the controller to ensure safe and high-performance flight. Simulations were taken at 0%, 10%, 30%, and 50% motor faults to test how effective the proposed FTC system is. After simulations, the controller’s real-time performance and reliability were validated through hardware-in-the-loop (HIL) experiments. The results validated that the proposed hybrid controller can guarantee stable flight and precision tracking of the desired trajectory when any single motor fails up to the order of 50%. It shows that the controller is of high fault tolerance and robustness, which will be a potential solution for improving the reliability of UAVs in fault-prone conditions. Full article

Vision navigation systems provide significant advantages in agricultural scenarios such as pesticide spraying, weeding, and harvesting by interpreting crop row structures in real-time to establish guidance lines. However, the delay introduced by image processing causes the path and pose information relied upon by the controller to lag behind the actual vehicle state. In this study, a hierarchical delay-compensated cooperative control framework (HDC-CC) was designed to synergize Model Predictive Control (MPC) and Sliding Mode Control (SMC), combining predictive optimization with robust stability enforcement for agricultural navigation. An upper-layer MPC module incorporated a novel delay state observer that compensated for visual latency by forward-predicting vehicle states using a 3-DoF dynamics model, generating optimized front-wheel steering angles under actuator constraints. Concurrently, a lower-layer SMC module ensured dynamic stability by computing additional yaw moments via adaptive sliding surfaces, with torque distribution optimized through quadratic programming. Under varying adhesion conditions tests demonstrated error reductions of 74.72% on high-adhesion road and 56.19% on low-adhesion surfaces. In Gazebo simulations of unstructured farmland environments, the proposed framework achieved an average path tracking error of only 0.091 m. The approach effectively overcame vision-controller mismatches through predictive compensation and hierarchical coordination, providing a robust solution for vision autonomous agricultural machinery navigation in various row-crop operations. Full article

This paper presents adaptive sliding mode observers (A-SMOs) performing speed estimation for sensorless induction motor drives utilized in both industrial and electrical vehicle (EV) applications due to their computational simplicity. The fact that the constant switching gain (${\lambda }_0$) is used in conventional SMOs (C-SMOs) leads to the chattering problem, especially in low-speed regions. To tackle this issue, this paper proposes two different ${\lambda }_0$ adaptation mechanisms based on fuzzy and curve fitting methods. To estimate stator stationary axis components of stator currents and rotor fluxes together with the rotor speed, the proposed A-SMOs only utilize the measured stator currents and voltages of the IM. Here, the difference only between the estimated and measured stator currents is determined as the sliding surface in the proposed A-SMOs. To demonstrate the effectiveness of the proposed fuzzy-based A-SMO (FA-SMO) and curve fitting-based A-SMO (CFA-SMO), they are compared with C-SMO in real-time experiments for different scenarios including wide speed range operations of IM with/without load torque changes. Moreover, the stator and rotor resistances as well as the magnetizing inductance variations are also examined in real-time experiments of the proposed methods and the conventional one. The estimation results demonstrate how positively the ${\lambda }_0$ adaptations in FA-SMO and CFA-SMO affect the performance of C-SMO. Finally, two A-SMOs with improved performance are introduced and verified through real-time experiments. Full article

This paper presents a fixed-time fault-tolerant control strategy based on an improved long short-term memory network for dynamic positioning of unmanned marine vehicles subject to signal quantization, disturbances, and input saturation. Firstly, an improved long short-term memory network optimized by an adaptive mixed-gradient algorithm is developed to accurately estimate external disturbances. Secondly, a fixed-time extended state observer is designed to rapidly predict thruster faults. Subsequently, within a fixed-time control framework, a novel terminal sliding-mode surface incorporating signal quantization parameters is constructed. In addition, a dynamic uniform quantization strategy with tunable sensitivity is introduced to effectively alleviate the performance degradation induced by quantization errors. Based on this, a fixed-time fault-tolerant controller is constructed. Finally, simulation results and comparative experiments are provided to demonstrate the effectiveness of the proposed control scheme. Full article