Search Results (35)

This paper proposes a robust barrier-function-based fuzzy adaptive super-twisting integral terminal sliding-mode control (BF-FAST-ITSMC) for robotic manipulators subject to external disturbances. Initially, an integral terminal sliding-mode manifold is designed to ensure finite-time error convergence and eliminate steady-state offsets. To reduce model dependence, the unknown nonlinear function is approximated and compensated using a fuzzy approximator. By combining the super-twisting algorithm (STA) and the barrier-function-based adaptive gains, the designed BF-FAST-ITSMC can suppress actuator chattering effectively, which allows control gains to increase automatically as the error approaches the prescribed boundary. This mechanism ensures that tracking errors are strictly confined within a predefined bound. Comparative simulations on an inverted pendulum and robotic manipulators with one to three degrees of freedom demonstrate that the proposed method provides superior tracking precision, smooth control torque, and enhanced robustness compared to conventional and fuzzy ITSMC schemes. Full article

Conventional maize fertilization suffers from uneven distribution, fertilizer waste, and environmental pollution. To address these issues and achieve precision fertilization for maize, a straight grooved-wheel fertilizer apparatus (SGWFA) was designed and optimized using the discrete element method (DEM). The blocking characteristic of the SGWFA was also evaluated. The optimal configuration (eight grooves, inner diameter of 26 mm) yielded a minimum discharge uniformity coefficient of variation of 2.50% and mild blocking, with a maximum total force of 161.884 N. Furthermore, a nonsingular terminal sliding mode control (NTSMC) algorithm was proposed for the speed loop of the brushless DC (BLDC) motor drive, while the current loop used conventional proportional-integral (PI) control. The overall system achieved dual closed-loop speed and current regulation with finite-time convergence of the speed tracking error. Simulations showed that, compared with conventional PI and fuzzy PI controllers, NTSMC had the smallest overshoot of 3.4%, the shortest settling time of 0.165 s, and the fastest disturbance rejection. Bench tests confirmed that the coefficient of variation under NTSMC was 2.85%, markedly better than fuzzy PI’s 3.15% and conventional PI’s 4.03%. It is also basically consistent with the simulation results. Field tests at 6, 9, and 12 km/h demonstrated over 95% per-row fertilization accuracy, with a maximum relative error of only 4.61%. This integrated system can effectively achieve precise fertilizer application under variable field conditions. Full article

Permanent magnet synchronous motor (PMSM)-based servo actuators are fundamental to high-performance electromechanical systems. However, in energy-sensitive aerospace applications, the impact of tracking error on system-level efficiency remains insufficiently quantified. This paper establishes an energy-oriented analytical framework linking PMSM tracking accuracy to vehicle-level energy consumption and flight range. By employing a specific mechanical energy formulation, we demonstrate that tracking deviations modify aerodynamic drag and introduce additional dissipative work. Specifically, the accumulated dissipation is shown to admit a lower bound proportional to the integral of the squared tracking error, from which a range degradation bound is derived. These results reveal that “tracking-error energy” imposes a fundamental limit on achievable flight distance. A Lyapunov-based analysis further proves that minimizing this error energy reduces total aerodynamic dissipation without requiring modifications to propulsion scheduling or guidance laws. Numerical simulations comparing a conventional sliding mode controller with an advanced fuzzy-adaptive nonsingular terminal sliding mode controller confirm that enhanced servo precision directly improves velocity retention and range performance. This framework offers practical insights for designing energy-aware PMSM control strategies in energy-constrained aerospace platforms. Full article

To address the chattering phenomenon and sensitivity to load disturbances in conventional sliding mode observers (SMO) for sensorless permanent magnet synchronous motor (PMSM) control, this paper proposes a robust sensorless control strategy integrating a fuzzy adaptive SMO with an improved sliding mode speed controller. In the observer design, a continuous hyperbolic tangent function, $tanh \left(ax\right)$, replaces the traditional sign function, while a fuzzy logic controller adaptively tunes the convergence factor a to enhance estimation accuracy and suppress high-frequency chattering. Simultaneously, an adaptive quadrature phase-locked loop (AQPLL) is incorporated to achieve adaptive matching across various operating conditions by updating parameters online, which effectively reduces phase delay and improves the dynamic performance of rotor position and speed estimation. Furthermore, a non-singular terminal sliding mode control (NTSMC) strategy is employed in the outer speed loop with a proposed segmented terminal reaching law. This law ensures rapid response in large-error regions and mitigates steady-state oscillations in small-error regions, thereby strengthening system robustness against load disturbances. The stability of the proposed system is rigorously verified via Lyapunov stability analysis. Simulation and experimental results demonstrate that the proposed approach significantly reduces speed and position estimation errors under varying speeds and sudden load changes compared to the conventional SMO-PI method, while effectively suppressing system chattering to confirm its engineering feasibility. Full article

This paper introduces a novel control framework for prescribed-time synchronization of higher-order nonlinear multi-agent systems (MAS) subject to parametric uncertainties and external disturbances. The proposed method integrates a fuzzy neural network (FNN) with a robust non-singular terminal sliding mode controller (NTSMC) to ensure leader–follower consensus within a user-defined time horizon, regardless of the initial conditions. The FNN is employed to approximate unknown nonlinearities online, while an adaptive update law ensures accurate compensation for uncertainty. A terminal sliding manifold is designed to enforce finite-time convergence, and Lyapunov-based analysis rigorously proves prescribed-time stability and boundedness of all closed-loop signals. Simulation studies on a leader–follower MAS with four nonlinear agents under directed communication topology demonstrate the superiority of the proposed approach over conventional sliding mode control, achieving faster convergence, enhanced robustness, and improved adaptability against system uncertainties and external perturbations. Full article

Permanent Magnet Synchronous Motors (PMSMs) exhibit inherent symmetry in their electromagnetic structure yet behave as nonlinear and strongly coupled systems that are susceptible to internal parameter perturbations and external disturbances, posing challenges to effective control under dynamic operating conditions. To address these issues, this paper proposes a sliding mode control strategy for PMSMs that integrates a Novel Adaptive Reaching Law (NARL) and an Improved Terminal Fuzzy Sliding Mode Disturbance Observer (IFTSMDO), denoted as SMC-NARL-IFTSMDO. The NARL is designed with a state-dependent dynamic gain adjustment mechanism and terminal attractive factor characteristics: it increases the gain to ensure fast convergence when the system state is far from the sliding mode surface, and adaptively attenuates the gain to suppress chattering when approaching the sliding mode surface, thereby balancing the contradiction between convergence speed and chattering in traditional sliding mode control. The IFTSMDO constructs a composite sliding mode surface incorporating error derivatives, terminal power terms, and saturation functions, which enhances the sensitivity of disturbance estimation in the small-error stage, avoids high-frequency chattering caused by sign functions, and provides accurate feedforward compensation for the speed loop controller to improve the system’s anti-disturbance capability. Additionally, the asymptotic stability of the proposed control strategy is strictly proven using the Lyapunov stability theory, laying a solid theoretical foundation for its application. Experiments are conducted on a TMS320F28379D DSP-based platform, and quantitative results show that compared with the traditional sliding mode control (SMC-TRL), the proposed strategy reduces the no-load startup response time by 60%, the steady-state speed fluctuation by 60%, and the speed fluctuation under load disturbance by 81.5%, fully demonstrating its superiority in dynamic response and anti-disturbance performance. Full article

This study proposes a fractional-order adaptive super-twisting sliding mode control (FO-ASTSMC) strategy to mitigate the difficulties arising from nonlinearity, uncertain parameters, and substantial external interferences during path-following operations of a hydraulic excavator working device. The developed approach merges a high-order sliding mode differentiator aimed at state observation, a fresh fractional-order sliding manifold that embeds a memory component for bolstering transient performance and equilibrium accuracy, together with an adaptable super-twisting coefficient. This adaptive gain eliminates the requirement for prior awareness of disturbance limits, all the while mitigating chattering effects and bolstering system robustness. Utilizing Lyapunov theory, the finite-time stability of the overall closed-loop framework has been thoroughly demonstrated. For controller verification, joint simulations employing AMESim and Simulink platforms were performed, pitting its efficacy against both terminal sliding mode control (TSMC) and adaptive fuzzy sliding mode control (AFSMC). In nominal scenarios, the FO-ASTSMC method yielded the lowest root mean square error (RMSE) along with maximum error (MAXE) across boom, arm, and bucket articulations, registering mean decreases of $60\%$ in RMSE and $58.2\%$ in MAXE when benchmarked against AFSMC, alongside $41.8\%$ in RMSE and $43.6\%$ in MAXE versus TSMC. Facing sudden variations in loading, it exhibited enhanced robustness, achieving reductions of $64.2\%$ in RMSE and $54.5\%$ in MAXE beyond AFSMC, as well as $39\%$ in RMSE and $36.5\%$ in MAXE in comparison to TSMC. Outcomes from the simulations affirm that the suggested controller exhibits elevated precision, formidable robustness, and good applicability to actuators, thereby highlighting its considerable promise for implementation in actual engineering scenarios. Full article

This paper proposes a novel intelligent switching control strategy for a five-bar lower limb exoskeleton. First, during the support phase, terminal sliding mode control (TSMC) is employed to ensure robust stability and high-torque amplification capabilities. Then, during the swing phase, a hybrid controller combining proportional-integral-derivative (PID) control and the adaptive neuro-fuzzy inference system (ANFIS) is implemented to generate natural and compliant leg movements. Finally, to achieve smooth transitions between phases, an intelligent switching algorithm based on multi-sensor information fusion is proposed. Simulation results demonstrate that the proposed strategy keeps trajectory tracking errors below 0.05 across all gait phases and achieves stable torque amplification ratios ranging from 1:6 to 1:10. This performance significantly reduces the user’s physical exertion. These findings validate the effectiveness of this control framework in improving the stability and comfort of human–machine interaction. Full article

High-speed aircraft actuators are critical for precise control of aerodynamic surfaces, demanding fast response, accuracy, and robustness against uncertainties and disturbances. However, the complex nonlinear dynamics of these systems pose significant challenges for conventional control methods. Sliding mode control (SMC) offers robust performance and rapid transient response but is hindered by chattering, which can degrade performance. To address this, this paper proposes an innovative nonlinear control strategy that integrates global nonsingular terminal sliding mode control (NTSMC) for finite-time convergence with fuzzy logic-based adaptive gain tuning to mitigate chattering and suppress oscillations. A prototype actuator and experimental platform were developed to validate the approach. Experimental results demonstrate superior dynamic response and disturbance rejection compared to traditional methods, highlighting the effectiveness of the proposed control strategy. Full article

This paper focused on the motion control of an underwater vehicle installed on a linear guide system, which is driven by two electric winches with wire ropes. The vehicle is subject to complex nonlinear time-varying disturbances and actuator input saturation effects during motion. A coupled dynamic model, incorporating an underwater vehicle, winches, and wire ropes, was established. Particular attention was paid to the nonlinear time-varying hydrodynamic disturbances acting on the underwater vehicle. The Kelvin–Voigt model was introduced to characterize the nonlinear dynamic behavior of the wire ropes, enabling the model to capture the dynamic response characteristics of traction forces. To tackle cross-coupling within the towing system, a differential tension coordination control method was proposed that simultaneously regulates system tension during motion control. For the vehicle dynamics model, a nonsingular fast-terminal sliding-mode (NFTSM) controller was designed to achieve high-precision position tracking control. An auxiliary dynamic compensator was incorporated to mitigate the impact of actuator input saturation. To handle time-varying disturbances, a fuzzy adaptive nonlinear disturbance observer (FANDO) is developed to perform feedforward compensation. Stability proof of the proposed algorithms was provided. Extensive numerical simulations demonstrate the effectiveness of the control strategies. Compared to the NFTSM without the disturbance observer the absolute mean value of the tracking error decreased by 76%, the absolute maximum value of the tracking error decreased by 67%, and the mean square error decreased by 93.5%. 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

In this paper, a global fast terminal fuzzy sliding mode control scheme based on the radial basis function (RBF) neural network is proposed for quadrotor unmanned aerial vehicle systems in the presence of external disturbances, system model uncertainty, and time-varying mass. Firstly, the dynamic model of the quadrotor is divided into two subsystems, i.e., an outer-loop control subsystem and an inner-loop control subsystem. Secondly, an adaptive sliding mode controller is used to control the outer-loop control subsystem, which includes the adaptive laws estimating the time-varying mass and external disturbances. In the inner-loop control subsystem, a global fast terminal fuzzy sliding mode controller, which is based on the RBF neural network, is designed to control the attitude of a quadrotor. In this method, the system model uncertainty is approximated using the RBF neural network. Simultaneously, an adaptive fuzzy controller is introduced to estimate the switching gain and eliminate external disturbances, and the chattering phenomenon is eliminated effectively. Finally, simulations are provided to demonstrate the effectiveness of the proposed control scheme. Full article

Aiming at the problems of jittering waveforms and poor power quality caused by external disturbances during the operation of a dual-pulse-width-modulation (PWM) converter, an improved terminal sliding mode control and an improved active disturbance rejection control (ADRC) are investigated. The method is based on mathematical models of grid-side and machine-side converters to design the controllers separately, and the balance between the two sides is maintained by the capacitor voltage. An improved terminal fuzzy sliding mode control and equivalent input disturbance (EID)-error-estimation-based active disturbance rejection control are presented on the grid side to improve the voltage response rate, and an improved support vector modulation (SVM)–direct torque control (DTC)–ADRC method is developed on the motor side to improve the robustness against disturbances. Finally, theoretical simulation experiments are built in MATLAB R2023a/Simulink to verify the effectiveness and superiority of this method. Full article

In addressing the control of asynchronous motors in the remote conductivity of fertigation machines, this study proposes a joint control strategy based on the Fast Terminal Sliding Mode Control-Disturbance Observer (FTSMC-DO) system for asynchronous motors. The goal is to enhance the dynamic performance and disturbance resistance of asynchronous motors, particularly under low-speed operating conditions. The approach involves refining the two-degree-of-freedom internal model controller using fractional-order functions to explicitly separate the controller’s robustness and tracking capabilities. To mitigate the motor’s sensitivity to external disturbances during variable speed operations, a load disturbance observer is introduced, employing hyperbolic tangent and Fal functions for real-time monitoring and compensation, seamlessly integrated into the sliding mode controller. To address issues related to low-speed chattering typically associated with sliding mode controllers, this study introduces a revised non-singular fast terminal sliding mode surface. Additionally, guided by fuzzy control principles, the study enables real-time selection of sliding mode approaching law parameters. Experimental results from the asynchronous motor control platform demonstrate that FTSMC-DO control significantly reduces adjustment time and speed fluctuations during operation, minimizing the impact of load disturbances on the system. The system exhibits robust disturbance rejection, improved robustness, and enhanced control capability. Furthermore, field tests validate the effectiveness of the FTSMC-DO system in regulating remote electrical conductivity (EC) levels. The control time is observed to be less than 120 s, overshoot less than 16.1%, and EC regulation within 0.2 mS·cm⁻¹ over a pipeline distance of 120 m. The FTSMC-DO control consistently achieves the desired EC levels with minimal fluctuation and overshoot, outperforming traditional PID and SMC methods. This high level of precision is crucial for ensuring optimal nutrient delivery and efficient water usage in agricultural irrigation systems, highlighting the system’s potential as a valuable tool in modern, sustainable farming practices. Full article

This article presents a new design method of energy management strategy with model-free DC-Bus voltage control for the fuel-cell/battery/supercapacitor hybrid electric vehicle (FCHEV) system to enhance the power performance, fuel consumption, and fuel cell lifetime by considering regulation of DC-bus voltage. First, an efficient frequency-separating based-energy management strategy (EMS) is designed using Harr wavelet transform (HWT), adaptive low-pass filter, and interval type–2 fuzzy controller (IT2FC) to determine the appropriate power distribution for different power sources. Second, the ultra-local model (ULM) is introduced to re-formulate the FCHEV system by the knowledge of the input and output signals. Then, a novel adaptive model-free integral terminal sliding mode control (AMFITSMC) based on nonlinear disturbance observer (NDO) is proposed to force the actual values of the DC-link bus voltage and the power source’s currents track their obtained reference trajectories, wherein the NDO is used to approximate the unknown dynamics of the ULM. Moreover, the Lyapunov theorem is used to verify the stability of AMFITSMC via a closed-loop system. Finally, the FCHEV system with the presented method is modeled on a Matlab/Simulink environment, and different driving schedules like WLTP, UDDS, and HWFET driving cycles are utilized for investigation. The corresponding simulation results show that the proposed technique provides better results than the other methods, such as operational mode strategy and fuzzy logic control, in terms of the reduction of fuel consumption and fuel cell power fluctuations. Full article