Search Results (93)

Rehabilitation devices such as actuated lower-limb exoskeletons can provide essential mobility assistance for pediatric patients with gait impairments. Enhancing their control systems under conditions of user variability and dynamic disturbances remains a significant challenge, particularly in active-assist modes. This study presents a human-in-the-loop control architecture for a pediatric lower-limb exoskeleton, combining outer-loop admittance control with robust inner-loop trajectory tracking via a non-singular terminal sliding-mode (NSTSM) controller. Designed for active-assist gait rehabilitation in children aged 8–12 years, the exoskeleton dynamically responds to user interaction forces while ensuring finite-time convergence under system uncertainties. To enhance adaptability, we augment the inner-loop control with a twin delayed deep deterministic policy gradient (TD3) reinforcement learning framework. The actor–critic RL agent tunes NSTSM gains in real-time, enabling personalized model-free adaptation to subject-specific gait dynamics and external disturbances. The numerical simulations show improved trajectory tracking, with RMSE reductions of 27.82% (hip) and 5.43% (knee), and IAE improvements of 40.85% and 10.20%, respectively, over the baseline NSTSM controller. The proposed approach also reduced the peak interaction torques across all the joints, suggesting more compliant and comfortable assistance for users. While minor degradation is observed at the ankle joint, the TD3-NSTSM controller demonstrates improved responsiveness and stability, particularly in high-load joints. This research contributes to advancing pediatric gait rehabilitation using RL-enhanced control, offering improved mobility support and adaptive rehabilitation outcomes. Full article

To enhance the speed control performance of the permanent magnet synchronous motor (PMSM) servo system, an improved sliding mode control method integrating a torque observer is presented. The current loop uses current feedback decoupling PID control, and the speed loop applies sliding mode control. In comparison to previous work in hybrid SMC using fuzzy logic and torque observers, this p proposes a hyperbolic tangent function in replacement of the signum function to solve the conflict between rapidity and chattering in the traditional exponential reaching law, and fuzzy and segmental self-tuning rules adjust relevant switching terms to reduce chattering and improve the sliding mode arrival process. A load torque observer is designed to enhance the system’s anti-interference ability by compensating the observed load torque to the current loop input. Simulation results show that compared with traditional sliding mode control with a load torque observer (SMC + LO), PID control with a load torque observer (PID + LO), and Active Disturbance Rejection Control (ADRC), the proposed strategy can track the desired speed in 0.032 s, has a dynamic deceleration of 2.7 r/min during sudden load increases, and has a recovery time of 0.011 s, while the others have relatively inferior performance. Finally, the model experiment is carried out, and the results of the experiment are basically consistent with the simulation results. Simulation and experimental results confirm the superiority of the proposed control strategy in improving the system’s comprehensive performance. Full article

The twin propeller system can be powered by a motor with dual-rotating rotors, which generally necessitates that both rotors run at the same speed to prevent rolling. The motor with dual-rotating rotors is popular for applications that benefit from high torque density and an axially compact form factor. In order to minimize the effects of load disturbances and internal parameter perturbations on the motor performance, this paper proposes a control strategy combining disturbance observer and sliding mode control (SMC) technologies to realize the purpose of both rotors rotating at the same speed. There are issues with the conventional proportional-integral (PI) control for load disturbances and motor parameter variations, whereas the SMC method has its invariant properties. Meanwhile, the system disturbances obtained by a disturbance observer are estimated to be used as feed-forward compensation for the SMC control in order to reduce the undesired chattering during the SMC control process. The validity and practicability of the control strategies proposed in this paper are demonstrated by both simulations and experiments. Full article

Addressing the shortcoming that steer-by-wire (SBW) system cannot directly transmit road feel, this study investigates a SBW system dynamics model, steering angle tracking control, and road feel simulation algorithm design. This study proposes a high-precision observer-based road feel simulation method that achieves road feel feedback torque design through the real-time estimation of system disturbance torque based on accurate front-wheel angle tracking. The methodology employs an improved nonlinear second-order sliding mode observer (INSOSMO) to estimate the system disturbance torque. This observer incorporates proportional–integral terms into the super-twisting algorithm to enhance dynamic response, replaces the sign function with a Sigmoid function to eliminate chattering, and utilizes the sparrow search algorithm (SSA) for global parameter optimization. Meanwhile, a two-stage filter combining a strong tracking Kalman filter (STKF) and first-order low-pass filtering processes the observer values to generate road feel feedback torque. Additionally, for the active return control of the steering wheel, a backstepping sliding mode control (BSSMC) integrated with an extended state observer (ESO) is employed, where the ESO enhances the robustness of BSSMC through real-time nonlinear disturbance estimation and compensation. MATLAB/Simulink-CarSim co-simulation demonstrates that, under sinusoidal testing, the INSOSMO reduces mean absolute error (MAE) by 34.7%, 62.5%, and 60.1% compared to the ESO, Kalman filter observer (KFO), and conventional sliding mode observer (SMO), respectively. The designed road feel feedback torque meets operational requirements. The active return controller maintains accurate steering wheel repositioning across various speed ranges. Full article

This study proposes a novel fuzzy disturbance observer (FDO)-augmented adaptive nonsingular terminal sliding mode control (NTSMC) framework for multi-joint robotic manipulators, addressing critical challenges in trajectory tracking precision and disturbance rejection. Unlike conventional disturbance observers requiring prior knowledge of disturbance bounds, the proposed FDO leverages fuzzy logic principles to dynamically estimate composite disturbances—including unmodeled dynamics, parameter perturbations, and external torque variations—without restrictive assumptions about disturbance derivatives. The control architecture achieves rapid finite-time convergence by integrating the FDO with a singularity-free terminal sliding manifold and an adaptive exponential reaching law while significantly suppressing chattering effects. Rigorous Lyapunov stability analysis confirms the uniform ultimate boundedness of tracking errors and disturbance estimation residuals. Comparative simulations on a 2-DOF robotic arm demonstrate a 97.28% reduction in root mean square tracking errors compared to PD-based alternatives and a 73.73% improvement over a nonlinear disturbance observer-enhanced NTSMC. Experimental validation on a physical three-joint manipulator platform reveals that the proposed method reduces torque oscillations by 58% under step-type disturbances while maintaining sub-millimeter tracking accuracy. The framework eliminates reliance on exact system models, offering a generalized solution for industrial manipulators operating under complex dynamic uncertainties. Full article

To address the issues of poor stability and susceptibility to external disturbances in traditional model reference adaptive systems (MRASs) for permanent magnet synchronous motors (PMSMs), this paper proposes a sliding mode control strategy based on an improved model reference adaptive observer. First, the dynamic equations of the PMSM are used as the reference model, while the stator current equations incorporating speed variables are constructed as the adjustable model. Subsequently, a novel adaptive law is designed using Popov’s hyperstability theory to enhance the estimation accuracy of rotor position. A fractional-order system was introduced to construct both a fractional-order sliding surface and reaching law. Subsequently, a comparative study was conducted between the conventional integral terminal sliding surface and the proposed novel sliding mode reaching law. The results demonstrate that the new reaching law can adaptively adjust the switching gain based on system state variables. Under sudden load increases, the improved system achieves a 25% reduction in settling time compared to conventional sliding mode control (SMC), along with a 44% decrease in maximum speed fluctuation and a 42% reduction in maximum torque ripple, significantly enhancing dynamic response performance. Furthermore, a variable-gain terminal sliding mode controller is derived, and the stability of the closed-loop control system is rigorously proven using Lyapunov theory. Finally, simulations verify the effectiveness and feasibility of the proposed control strategy in improving system robustness and disturbance rejection capability. Full article

In this paper, a real-time assistive torque controller based on sliding-mode control is proposed for a Series Elastic Actuator (SEA)-driven lower limb assistive exoskeleton. To address the problem of the lack of buffering properties and the uneven torque output in traditional exoskeletons, a novel SEA is designed for the hip joint lower-limb exoskeleton. This structure features excellent cushioning properties and smooth torque output. On this basis, to enhance the torque tracking performance of the hip joint exoskeleton, in this study, a robust composite control strategy is proposed, which can maintain accuracy in the presence of unknown external disturbances and model parameter inaccuracies. The strategy consists of an adaptive phase oscillator for outputting the phase of the gait, a single-peak curve to provide a reference assistive torque, and a low-level controller to track the torque. The low-level controller employs Continuous Sliding-Mode Control (CSMC) to obtain a continuous control law and utilizes an Extended State Observer (ESO) to estimate the lumped disturbance. It ensures that the tracking error is asymptotically convergent with minimized chatter. The closed-loop stability of the system is theoretically proven by the Lyapunov method. The validity of the proposed algorithm is validated on a designed exoskeleton. Full article

In the context of the new energy hybrid ship propulsion system (NE-HSPS), the parameters of the rotor speed, torque, and current of the permanent magnet synchronous motor (PMSM) are susceptible to environmental variations and unmodeled disturbances. Conventional nonlinear controllers (e.g., backstepping, PI, and sliding mode) encounter challenges related to response speed, interference immunity, and vibration jitter. These challenges stem from the inherent uncertainties in perturbations and the limitations of the traditional nonlinear controllers. In this paper, a novel Adaptive Finite-Time Command-Filtered Backstepping Controller (AFTCFBC) is proposed, featuring a faster response time and the elimination of overshoot. The proposed controller is a significant advancement in the field, addressing the computational complexity of backstepping control and reducing the maximum steady-state error of the control output. The novel controller incorporates a Nonlinear Finite-Time Command Filter (NFTCF) adapted to the variation in motor speed. Secondly, a novel Nonlinear Sliding Mode Observer (NSMO) is proposed based on the designed nonlinear sliding mode gain function (φ(S_w)) to estimate the load disturbance of the electric propulsion system. The Uncertainty Parameter-Adaptive law (UPAL) is designed based on Lyapunov theory to improve the robust performance of the system. The construction of a simulation model of a hybrid ship PMSM under four distinct working conditions, including constant speed and constant torque, the lifting and lowering of speed, loading and unloading, and white noise interference, is presented. The results of this study demonstrate a significant reduction in speed-tracking overshoot to zero, a substantial decrease in integral squared error by 90.15%, and a notable improvement in response time by 18.6%. Full article

In remote conductivity control for water–fertilizer integration systems, challenges such as long-distance nonlinearities and variable parameters can lead to fertilization inaccuracies, including over-irrigation and uneven distribution, affecting both productivity and environmental sustainability. To mitigate these issues, this study proposes a variable-parameter sliding mode control (VSMC) strategy, combined with an adaptive observer based on Recursive Least Squares (RLS) to estimate system inertia and load torque in real time. This allows for dynamic adjustment of the sliding surface parameters, ensuring robust control even under varying operating conditions. Two parameter derivation approaches—analytical modeling and data-driven fitting—are evaluated. Field tests demonstrate that VSMC outperforms the Proportional–Integral (PI) and conventional sliding mode control (SMC) methods in maintaining target electrical conductivity (EC) levels. Specifically, for a target EC of 1.4 mS/cm, VSMC stabilizes the system to within 1.18–1.60 mS/cm in 95 s, with a 14.3% overshoot, well within agronomic tolerance. In regional irrigation trials, VSMC significantly improves fertilizer uniformity, reducing the standard deviation of potassium nitrate distribution from 2.14 (PI) to 0.59. The simulation and experimental results validate the effectiveness and robustness of the proposed method, highlighting its potential to enhance agronomic efficiency and reduce environmental impact. Full article

To suppress current and torque ripples, this paper proposes a novel deadbeat predictive current control strategy based on an adaptive sliding mode observer for permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) drives. The parameter sensitivity of predictive current control is analyzed, and a sliding mode observer is employed to calculate the parameter disturbances for voltage compensation. The predicted current is utilized instead of the sampled current to address the one-step delay issue, effectively suppressing the adverse effects of parameter mismatch in predictive control. The adaptive control parameter module suppresses the chattering phenomenon in sliding mode control and enhances the observer’s adaptability under varying load conditions. The effectiveness of the proposed strategy is validated on a 2.2 kW PMa-SynRM platform. This strategy can suppress current and torque fluctuations under complex operating conditions, which has significant implications for electric vehicle drive control. Full article

A novel sliding mode control (SMC) strategy incorporating an adaptive super-twisting algorithm is developed for permanent magnet synchronous motors (PMSMs), effectively mitigating high-frequency chattering while enhancing external disturbance rejection capabilities. Initially, a sliding surface is crafted based on the dynamic characteristics of the PMSM and real-time feedback. The super-twisting algorithm is subsequently applied adaptively to dynamically adjust the control effort required to maintain the sliding mode state, thereby ensuring precise and prompt intervention to uphold system stability and enhance response speed. Additionally, in light of operational challenges such as road-induced load disturbances, a Lyapunov-based disturbance observer is proposed for precise load torque estimation in PMSM systems. The efficacy of the proposed control and observation methods is substantiated through a hardware-in-the-loop experiment test, demonstrating that the developed sliding mode controller, leveraging the adaptive super-twisting algorithm, exhibits superior tracking and disturbance rejection capabilities, reduces steady-state current error, and bolsters system parameter robustness, and the modified extended state observer (MESO) exhibits commendable estimation performance. Full article

The present paper proposes a new Maximum Torque Per Ampere (MTPA) algorithm applied to sensorless speed control for the Synchronous Reluctance Machine (SynRM). The SynRM mathematical model is suitably modified and expressed in the γδ estimated reference frame, which could be applied in sensorless implementations. In the controller–observer scheme, an MTPA controller is coupled with a sliding mode observer (SMO) of first order. The provided equivalent control inputs are directly utilized by a modified EMF observer to estimate the rotor speed and position. Also, the MTPA control, SMO, and modified EMF observer are accordingly expressed in the γδ reference frame. In the duration of the SynRM operation, the developed MTPA algorithm succeeds in adjusting both stator current components in the γ-axis and δ-axis to the maximum torque point, while the SMO converges rapidly, achieving the coincidence between the γδ and dq reference frames. In addition, a simple torque decoupling technique is used to determine the γ-axis and δ-axis reference currents connected with the Anti-Windup Controller (AWC) for stator current control. Despite conventional MTPA methods, the proposed MTPA control strategy is designed to be robust in a wide speed range, exhibiting a high dynamic performance, regardless of the presence of external torque disturbances, reference speed variation, and even current measurement noise. The performance of the overall observer–control system is examined and evaluated using MATLAB/Simulink and considering noisy current feedback. Simulation results demonstrate the robustness and effectiveness of the proposed MTPA-based control method. Full article

To enhance the speed-control performance of a permanent magnet synchronous motor (PMSM) drive system, an improved sliding-mode anti-interference control strategy is presented. Firstly, to tackle the speed fluctuation issue caused by cogging torque (a periodic disturbance) and time-varying disturbances at low set speeds in PMSM, an improved sliding-mode control (ISMC) is proposed. It consists of a continuous adaptive fast terminal sliding-mode surface (CAFTSMS) and a new reaching law (NRL). The CAFTSMS boosts the system’s immunity to interference, while the NRL, improved via an adaptive function, enhances the fast transient response and notably reduces speed fluctuations. Secondly, a quasi-proportional resonant (QPR) controller is introduced. It suppresses specific-order system harmonics, significantly reducing the harmonic amplitude and strengthening the system’s ability to handle periodic disturbances. Finally, a cascaded extended state observer (CESO) with a special cascade structure is proposed to solve the observation-delay problem in the traditional cascade structure. Experimental results show that the proposed sliding-mode anti-disturbance control strategy performs excellently in overcoming disturbances. Full article

To improve the synchronization accuracy of dual motors under external disturbances, this paper proposes a cross-coupling control strategy based on an improved global fast terminal sliding mode control (GFTSMC) and disturbance observer (DOB). In practical applications, dual-motor systems are often affected by external disturbances, leading to synchronization errors between the motors, which in turn affect the system’s stability and accuracy. First, for single-motor control, this paper uses the improved GFTSMC method to design a speed loop, enhancing the tracking accuracy and dynamic response of the individual motor by optimizing the sliding surface. Then, the improved GFTSMC is combined with a cross-coupling strategy to effectively solve the synchronization problem of dual motors. The cross-coupling strategy coordinates the operation of the two motors, reducing the speed deviation between them, thus improving synchronization accuracy and enhancing the system’s disturbance rejection capability. Moreover, the DOB is used to precisely estimate the frictional torque, and compensating for these disturbances improves the system’s robustness and stability. The results show that the proposed control method significantly improves the speed synchronization of the dual motors and exhibits excellent dynamic performance, effectively coping with complex external disturbances. Full article

This paper addresses the problem of large-angle attitude maneuvering and tracking control for rigid spacecraft, considering angular velocity and torque constraints, actuator faults, and external disturbances. First, a sliding-mode-like vector is constructed to guarantee the satisfaction of the angular velocity constraints. A modified preassigned finite-time function, which can adaptively adjust the boundaries, is then proposed to constrain the sliding-mode-like vector. The controller is designed to stabilize the closed-loop system using a barrier Lyapunov function. Additionally, actuator saturation is compensated adaptively, and the system’s lumped disturbance is estimated using a fixed-time disturbance observer. Finally, the practically preassigned finite-time stability of the closed-loop system is demonstrated. In practical applications, the proposed controller can guarantee transient and steady-state performance, prevent excessive angular velocity, and ensure compliance with the physical limitations of the actuators. Simulation results are provided to demonstrate the effectiveness of the proposed controller. Full article