Search Results (138)

This paper proposes an adaptive wavelet neural network nonsingular fast terminal sliding mode control strategy based on a finite-time framework for a space robot system under external disturbances and model uncertainties. Firstly, the dynamic model of space robot is established based on the second Lagrange equation. Unlike sliding mode control, which converges asymptotically, terminal sliding mode control (TSMC) has been proposed to ensure finite-time convergence for a space robot system. Based on the aforementioned TSMC framework, the fast terminal sliding mode control (FTSMC) is proposed to enhance system convergence rate. However, TSMC exhibits a singularity issue attributed to the presence of negative fractional order. To avoid this issue, a nonsingular fast terminal sliding mode controller (NFTSMC) has been proposed. The controller is designed to integrate linear and nonlinear terms into a novel nonsingular fast terminal sliding mode surface. The method achieves fast finite-time convergence concurrently with improved robustness, while effectively avoiding singularities. To compensate for external disturbances and model uncertainties in the space robot system, this paper proposes the combination of wavelet neural network (WNN) for the real-time estimation of lumped uncertainties. Network parameters are dynamically adjusted via an adaptive law to mitigate chattering effectively and enhance trajectory tracking precision. Utilizing Lyapunov stability theory and numerical simulations, the space robot system’s stability is rigorously proven and the controller effectiveness is validated. Compared with the traditional NFTSMC, the proposed control strategy reduces the convergence time by 20.74%. In the case of trajectory tracking comparison, the root mean square error (RMSE) improves by 35.85%, the mean tracking error improves by 63.29%, the integral of absolute error (IAE) improves by 29.37%, and the integral of time-weighted absolute error (ITAE) improves by 93.06%. Additionally, a comparative simulation with RBFNN is included in this paper. Compared with RBFNN, the proposed control strategy reduces input torque energy consumption by 77.36% and improves control smoothness by 87.03%, quantitatively demonstrating the effectiveness of the proposed control strategy. Full article

The tension control of carbon fiber diagonal weaving looms is severely affected by the coupling between structured friction and unstructured disturbances, leading to strong nonlinearities and time-varying uncertainties. To overcome the chattering and model-dependency issues inherent in traditional sliding mode control, a nonlinear dynamic model incorporating the Stribeck friction term was established. An Improved Adaptive Radial Basis Function-based Nonsingular Fast Terminal Sliding Mode Control (I-ARBF-NFTSMC) framework was then proposed. The framework adopts a divide-and-conquer composite compensation mechanism, in which a smooth Hyperbolic Tanh Fixed-Time Disturbance Observer (Tanh-FTDO) estimates external disturbances and suppresses chattering, and an Improved Adaptive Radial Basis Function (I-ARBF) neural network approximates and compensates internal nonlinear friction. Simulation results show that, compared with the conventional Fixed-Time Extended State Observer-based method (FESO-NFTSMC), the proposed controller achieves higher disturbance-estimation accuracy and tracking performance under sinusoidal, triangular, and composite disturbances. In composite-disturbance conditions, the steady-state mean-squared error is reduced by about 60%, the maximum tracking error decreases from 0.08787 N to 0.01965 N, and the settling time shortens by approximately 25.2%, while effectively mitigating high-frequency chattering. The proposed strategy achieves fast finite-time convergence with enhanced smoothness and robustness, providing a real-time executable solution for high-precision tension control in complex nonlinear weaving processes. Full article

This study introduces a sensorless control approach for permanent magnet synchronous motors (PMSMs) that employs an Improved Non-Singular Fast Terminal Sliding Mode Controller (IMNFTSMC) and an Improved Non-Singular Fast Terminal Sliding Mode Observer (IMNFTSMO). The IMNFTSMC employs a novel hybrid reaching law and a continuous piecewise square root switching function to achieve faster convergence and effective chattering reduction over the conventional Sliding Mode Controller (SMC). This design successfully replaces two critical components: the discontinuous constant velocity term (a key component of the traditional SMC reaching law that is a primary source of control chattering in PMSM torque regulation) and the high-gain exponential term (which tends to induce overshoot during transient speed adjustments and degrade steady-state control precision). In the IMNFTSMO, a hybrid approach combining linear and non-singular terminal sliding modes eliminates phase lag associated with low-pass filtering in traditional sliding mode observers, improving rotor position and speed estimation accuracy. Stability of both IMNFTSMC and IMNFTSMO is rigorously proven using Lyapunov stability theory.Validation through extensive simulations and hardware experiments, including challenging zero-speed start, speed stepping, and load disturbance tests, confirms the proposed strategy provides improved dynamic response, effective anti-disturbance capability, and high accuracy for rotor position and speed estimation compared to established benchmark methods, demonstrating its feasibility for mid-to-low speed sensorless PMSM drives. Full article

To address trajectory tracking of cable-driven continuum robots (CDCRs) in the presence of obstacles, this paper proposes an integrated control framework that combines online trajectory replanning, obstacle avoidance, and tracking control. The control system consists of two modules. The first is a trajectory replanning controller developed on an improved model predictive control (IMPC) framework. The second is a trajectory-tracking controller that integrates an adaptive disturbance observer with a fast non-singular terminal sliding mode control (ADO-FNTSMC) strategy. The IMPC trajectory replanning controller updates the trajectory of the CDCRs to avoid collisions with obstacles. In the ADO-FNTSMC strategy, the adaptive disturbance observer (ADO) compensates for uncertain dynamic factors, including parametric uncertainties, unmodeled dynamics, and external disturbances, thereby enhancing the system’s robustness and improving trajectory tracking accuracy. Meanwhile, the fast non-singular terminal sliding mode control (FNTSMC) guarantees fast, stable, and accurate trajectory tracking. The average tracking errors for IMPC-ADO-FNTSMC, MPC-FNTSMC, and MPC-SMC are 1.185 cm, 1.540 cm, and 1.855 cm, with corresponding standard deviations of 0.035 cm, 0.057 cm, and 0.078 cm in the experimental results. Compared with MPC-FNTSMC and MPC-SMC, the IMPC-ADO-FNTSMC controller reduces average tracking errors by 29.96% and 56.54%. Simulation and experimental results demonstrate that the designed two-module controller (IMPC-ADO-FNTSMC) achieves fast, stable, and accurate trajectory tracking in the presence of obstacles and uncertain dynamic conditions. Full article

To enhance line capacity in high-speed railways without new infrastructure, virtual coupling train sets (VCTSs) enable reduced inter-train distances via real-time communication and cooperative control. However, unknown disturbances and model uncertainties challenge VCTS performance, often causing chattering, slow convergence, and poor disturbance rejection. This paper proposes a novel finite-time extended state observer-based nonsingular terminal sliding mode (FTESO-NTSM) control strategy. The method integrates a nonsingular terminal sliding mode surface with a hyperbolic tangent-based reaching law to ensure fast convergence and chattering suppression, while a finite-time extended state observer estimates and compensates for lumped disturbances in real time. Lyapunov analysis rigorously proves finite-time stability. Numerical simulations under different initial statuses are conducted to validate the effectiveness of the proposed method. The results show that the maximum observation error achieves 0.0087 kN. The speed chattering magnitudes reach 0.00087 km/h, 0.0017 km/h, 0.0026 km/h, and 0.0034 km/h for the leading train and three followers, respectively. Furthermore, the convergence time of the followers is 56 s, 130 s, and 76 s, respectively. The results highlight that the proposed method can significantly improve line capacity and transportation efficiency. Full article

To achieve high-precision trajectory tracking for multi-joint robotic manipulators in the presence of model uncertainties, external disturbances, and strong coupling effects, this paper proposes a nonsingular fast terminal sliding mode control (NFTSMC) scheme incorporating an extended Kalman filter-based disturbance observer. First, the Kalman filter is combined with an extended state observer to perform the real-time observation of both internal and external disturbances in the system, accurately estimating system uncertainty and external disturbances. This approach reduces noise interference while significantly improving the correction accuracy of position and tracking errors. Second, an improved nonsingular fast terminal sliding mode controller with an optimized convergence law is introduced to ensure stability during the tracking process, effectively mitigate oscillation phenomena, and accelerate the system’s convergence speed. Finally, the convergence of the proposed method is analyzed by constructing an appropriate Lyapunov function. Simulation and experimental results strongly validate the superior performance of the proposed control strategy, demonstrating that the system can achieve high-precision trajectory tracking under the complex coupled effects of a six-axis robotic manipulator, and exhibits significant advantages in terms of accuracy and robustness. Full article

High-precision torque regulation is essential to ensure reaction wheel systems meet the stringent attitude control requirements of modern spacecraft. In three-phase half-bridge brushless DC (BLDC) drives, non-ideal back-electromotive force (back-EMF) waveforms cause pronounced conduction interval torque ripple, leading to inaccurate and unstable output torque. To address this problem, this article proposes a composite torque control strategy integrating an Adaptive Nonsingular Fast Terminal Sliding-Mode Observer (ANFTSMO) with an Adaptive Sliding-Mode Controller (ASMC). The ANFTSMO achieves precise back-EMF estimation and electromagnetic torque reconstruction by eliminating singularities, reducing chattering, and adaptively adjusting observer gains. Meanwhile, the ASMC employs an adaptive switching gain function to achieve asymptotic current convergence with suppressed chattering, thereby ensuring accurate current tracking. System stability is verified via Lyapunov analysis. Simulation and experimental results demonstrate that, compared with conventional constant-current control, the torque smoothness and disturbance rejection of the proposed method are improved, enabling precise and stable reaction wheel torque delivery for high-accuracy spacecraft attitude regulation. Full article

This work proposes a non-singular fast terminal sliding mode control (NFTSMC) strategy based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and a nonlinear disturbance observer (NDO) to address the issues of modeling errors, motion disturbances, and transmission friction in robotic manipulators. Firstly, a novel modular serial 5-DOF robotic manipulator configuration is designed, and its kinematic and dynamic models are established. Secondly, a nonlinear disturbance observer is employed to estimate the total disturbance of the system and apply feedforward compensation. Based on boundary layer technology, an improved NFTSMC method is proposed to accelerate the convergence of tracking errors, reduce chattering, and avoid singularity issues inherent in traditional terminal sliding mode control. The stability of the designed control system is proved using Lyapunov stability theory. Subsequently, a deep reinforcement learning (DRL) agent based on the TD3 algorithm is trained to adaptively adjust the control gains of the non-singular fast terminal sliding mode controller. The dynamic information of the robotic manipulator is used as the input to the TD3 agent, which searches for optimal controller parameters within a continuous action space. A composite reward function is designed to ensure the stable and efficient learning of the TD3 agent. Finally, the motion characteristics of three joints for the designed 5-DOF robotic manipulator are analyzed. The results show that compared to the non-singular fast terminal sliding mode control algorithm based on a nonlinear disturbance observer (NDONFT), the non-singular fast terminal sliding mode control algorithm integrating a nonlinear disturbance observer and the Twin Delayed Deep Deterministic Policy Gradient algorithm (TD3NDONFT) reduces the mean absolute error of position tracking for the three joints by 7.14%, 19.94%, and 6.14%, respectively, and reduces the mean absolute error of velocity tracking by 1.78%, 9.10%, and 2.11%, respectively. These results verify the effectiveness of the proposed algorithm in enhancing the trajectory tracking accuracy of the robotic manipulator under unknown time-varying disturbances and demonstrate its strong robustness against sudden disturbances. Full article

Quadrotor UAVs benefit from control strategies that can deliver rapid convergence and strong robustness in order to fully exploit their high agility. Finite-time control based on terminal sliding modes has been recognized as an effective alternative to classical sliding mode control, which only guarantees asymptotic convergence. Its enhanced variant, nonsingular fast terminal sliding mode control, eliminates singularities and achieves accelerated convergence; however, chattering-induced high-frequency oscillations remain a major concern. To address this issue, this study introduces a hybrid control framework that combines the super-twisting algorithm with ${\mathcal{L}}_1$ adaptive control. The super-twisting component preserves the robustness of sliding mode control while mitigating chattering, whereas ${\mathcal{L}}_1$ adaptive control provides rapid online estimation and compensation of model uncertainties and unknown disturbances. The resulting scheme is implemented in a quadrotor flight-control architecture and evaluated through numerical simulations. The results show that the proposed controller offers faster convergence and enhanced robustness relative to existing approaches, particularly in the presence of wind perturbations, periodic obstacle-avoidance maneuvers, and abrupt partial loss of propeller thrust. Full article

A fast and stable flight control system is crucial for improving the efficiency of unmanned aerial vehicle (UAV) missions. Focusing on the trajectory tracking control of quadrotor UAVs, this paper proposes a trajectory tracking control method based on the global fast terminal sliding mode control (GFTSMC) algorithm to address the slow response speed and insufficient anti-disturbance capability inherent in the widely used Proportional–Integral–Derivative (PID) control algorithm and conventional sliding mode control (SMC) algorithm. Firstly, considering the gyroscopic moment of a quadrotor UAV’s rotors, an accurate kinematic and dynamic model of a quadrotor UAV is established, and the trajectory tracking problem faced by such UAVs is decoupled into the command tracking problems of the position loop and the attitude loop. Secondly, GFTSMC controllers are designed for these loops, and the Lyapunov principle is adopted to prove the stability of the designed controllers. Finally, simulation verification is carried out. The simulation results show that, compared to PID control, GFTSMC-based trajectory tracking control for quadrotor UAVs exhibits the characteristics of no overshoot, higher tracking accuracy, and stronger anti-disturbance capability. Compared to nonsingular terminal sliding mode control (NTSMC) and SMC, GFTSMC-based trajectory tracking control reduces the steady-state convergence time by 33.8% and 36.5% and the steady-state disturbance error by 83.1% and 97.3%, respectively, demonstrating faster response speed and stronger anti-disturbance capability. Therefore, the application of GFTSMC significantly improves the trajectory tracking control performance of quadrotor UAVs, thereby supporting them in performing operations in scenarios requiring high real-time performance, precision, and anti-disturbance capability. Full article

Most control strategies for magnetic bearings are typically formulated upon the linearized suspension force model, and the nonlinear characteristics are neglected or regarded as the disturbance and variation in parameters of the control system. The controllers based on linearized suspension force model struggle to achieve fast response under disturbance. Therefore, a nonlinear mathematic model that simultaneously represents the main nonlinearity of suspension force and facilitates the design of high-performance controller is necessary to establish. In this study, a new mathematical model of suspension force with varying current stiffness is developed, and a specific controller was designed based on this model. Firstly, the nonlinear mathematical model of six-pole radial–axial hybrid magnetic bearing (RAHMB) is established. Secondly, the characteristics of the current stiffness varying with rotor displacement are analyzed and the expression between current stiffness and rotor displacement is fitted. Then, the linearized model is built via Taylor expansion of the nonlinear model. Subsequently, the varying current stiffness model is constructed by substituting the fitted expression of varying current stiffness into linearized model. Finally, an adaptive nonsingular terminal sliding mode controller (ANTSMC) is designed based on the proposed varying current stiffness model. The simulation and experiment results have shown that the ANTSMC based on varying current stiffness model reduces chattering more than 64% and reduces convergence time more than 70% to the NTSMC based on the linearized model. Full article

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

Magnetically levitated artificial hearts impose stringent requirements on the blood-pump motor: zero friction, minimal heat generation and full biocompatibility. Traditional mechanical-bearing motors and permanent-magnet bearingless motors fail to satisfy all of these demands simultaneously. A bearingless switched reluctance motor (BSRM), whose rotor contains no permanent magnets, offers a simple structure, high thermal tolerance, and inherent fault-tolerance, making it an ideal drive for implantable circulatory support. This paper proposes an 18/15/6-pole dual-stator BSRM (DSBSRM) that spatially separates the torque and levitation flux paths, enabling independent, high-precision control of both functions. To suppress torque ripple induced by pulsatile blood flow, a variable-overlap TSF-PWM-DITC strategy is developed that optimizes commutation angles online. In addition, a grey-wolf-optimized fast non-singular terminal sliding-mode controller (NRLTSMC) is introduced to shorten rotor displacement–error convergence time and to enhance suspension robustness against hydraulic disturbances. Co-simulation results under typical artificial heart operating conditions show noticeable reductions in torque ripple and speed fluctuation, as well as smaller rotor radial positioning error, validating the proposed motor and control scheme as a high-performance, biocompatible, and reliable drive solution for next-generation magnetically levitated artificial hearts. Full article

With the rapid development of deep-sea resource exploration and marine scientific research, wheeled remotely operated vehicles (ROVs) have become crucial for seabed operations. However, under complex seabed conditions, traditional ROV control systems suffer from insufficient trajectory tracking accuracy, poor disturbance rejection capability, and low dynamic torque distribution efficiency. These issues lead to poor motion stability and high energy consumption on sloped terrains and soft substrates, which limits the effectiveness of deep-sea engineering. To address this, we proposed a comprehensive motion control solution for deep-sea wheeled ROVs. To improve modeling accuracy, a coupled kinematic and dynamic model was developed, together with a body-to-terrain coordinate frame transformation. Based on rigid-body kinematics, three-degree-of-freedom kinematic equations incorporating the slip ratio and sideslip angle were derived. By integrating hydrodynamic effects, seabed reaction forces, the Janosi soil model, and the impact of subsidence depth, a dynamic model that reflects nonlinear wheel–seabed interactions was established. For optimizing disturbance rejection and trajectory tracking, a hierarchical control method was designed. At the kinematic level, an improved model predictive control framework with terminal constraints and quadratic programming was adopted. At the dynamic level, non-singular fast terminal sliding mode control combined with a fixed-time nonlinear observer enabled rapid disturbance estimation. Additionally, a dynamic torque distribution algorithm enhanced traction performance and trajectory tracking accuracy. Full article

This article introduces a novel decentralized compliance control technique designed to manage the behavior of multi-axle heavy vehicles equipped with electro-hydraulic actuator suspension systems on uneven terrains. To address the challenges of controller design complexity and network communication burden in large-scale active suspension systems for multi-axle heavy vehicles, the decentralized scheme proposed in this paper decomposes the overall vehicle control problem into decentralized compliance control tasks for multiple electro-hydraulic actuator suspension subsystems (MEHASS), each responding to road disturbances. The position-based compliance control strategy consists of an outer-loop generalized impedance controller (GIC) and an inner-loop position controller. The GIC, which offers explicit force-tracking performance, is employed to define the dynamic interaction between each wheel and the uneven road surface, thereby generating the vertical trajectory for the MEHASS. This design effectively reduces vertical vibration transmission to the vehicle chassis, improving ride comfort. To handle external disturbances and enhance control accuracy, the position control employs a nonsingular fast integral terminal sliding mode controller. Furthermore, a three-axle heavy vehicle prototype with electro-hydraulic actuator suspension is developed for on-road driving experiments. The effectiveness of the proposed control method in enhancing ride comfort is demonstrated through comparative experiments. Full article