Search Results (902)

Mechanical ventilation is indispensable for patients with severe respiratory conditions, and high-fidelity lung simulators play a pivotal role in ventilator testing, clinical training, and respiratory research. However, most existing simulators are passive, single-lung models with limited and discrete control over respiratory mechanics, which constrains their ability to reproduce realistic breathing dynamics. To overcome these limitations, this study presents a dual-chamber lung simulator that can operate in both active and passive modes. The system integrates a sliding mode controller enhanced by a linear extended state observer, enabling the accurate replication of complex respiratory patterns. In active mode, the simulator allows for the precise tuning of respiratory muscle force profiles, lung compliance, and airway resistance to generate physiologically accurate flow and pressure waveforms. Notably, it can effectively simulate pathological conditions such as acute respiratory distress syndrome (ARDS) and chronic obstructive pulmonary disease (COPD) by adjusting key parameters to mimic the characteristic respiratory mechanics of these disorders. Experimental results show that the absolute flow error remains within ±3L/min, and the response time is under 200ms, ensuring rapid and reliable performance. In passive mode, the simulator emulates ventilator-dependent conditions, providing continuous adjustability of lung compliance from 30 to 100mL/cmH${}_2$O and airway resistance from 2.01 to 14.67$\sqrt{{\mathrm{cmH}}_2\mathrm{O}}/(\mathrm{L}/\mathrm{s})$, with compliance deviations limited to ±5%. This design facilitates fine, continuous modulation of key respiratory parameters, making the system well-suited for evaluating ventilator performance, conducting human–machine interaction studies, and simulating pathological respiratory states. Full article

In this paper, an adaptive sliding mode fault-tolerant control (FTC) scheme is proposed for small Quadrotor Unmanned Aerial Vehicles (QUAVs) used in education and teaching formation in the presence of systematic unknown external disturbances with actuator failures. A radial basis function neural network (RBFNN) is employed to handle the nonlinear interaction function, and a fault-tolerant-based NN extended state observer (NNESO) is designed to estimate the unknown external disturbance. Meanwhile, an adaptive fault observer is developed to estimate and compensate for the fault parameters of the system. To achieve satisfactory trajectory tracking performance for the QUAV, an adaptive sliding mode control (SMC) strategy is designed. This strategy mitigates the strong coupling effects among the design parameters within the QUAV formation. The stability of the closed-loop system is rigorously demonstrated by Lyapunov analysis, and the controlled QUAV formation can achieve the desired tracking position. Simulation results verify the effectiveness of the proposed control method. Full article

Sliding mode control (SMC) provides robustness and disturbance rejection in permanent magnet synchronous motor (PMSM) control but faces the challenge of speed degradation during sudden load disturbance changes without a load observer. This paper proposes a backpropagation neural network-adjusted improved SMC (BPNN-ISMC). A simplified PMSM model is established by ignoring the disturbance term. An improved arrival law is developed by optimizing the constant-speed approach term of the traditional exponential arrival law and embedding an adaptive term. A BPNN is designed with performance metrics including speed error, its derivative, and maximum error to improve training efficiency. Speed/position estimation combines a sliding mode observer with an extended Kalman filter to suppress jitter. Simulation results demonstrate the significant advantages of the BPNN-ISMC method: in set-point control, overshoot suppression is evident, and the relative error during the stable phase after sudden load disturbance increases is reduced by 93.62% compared to the ISMC method and by 99.80% compared to the SMC method. Compared to the ADRC method, although the steady-state errors are the same, the BPNN-ISMC method exhibits smaller speed fluctuations during sudden changes. In servo control, the root mean square error of speed tracking is reduced by 18.83% compared to the ISMC method, by 89.70% compared to the SMC method, and by 37.14% compared to the ADRC method. This confirms the dynamic performance improvement achieved through adaptive adjustment of neural network parameters. Full article

The permanent magnetic synchronous motor (PMSM) is of significant use for the centrifugal hydrogen compressor (CHC) in the hydrogen fuel cell system. In order to satisfy the demand for improving the CHC’s performance, including higher accuracy, higher response speed, and wider speed range, this paper proposes a novel adaptive super-twisting sliding mode observer (ASTSMO)-based position sensorless control strategy for the highspeed PMSM. Firstly, the super-twisting algorithm (STA) is introduced to the sliding mode observer (SMO) to reduce chattering and improve the accuracy of position estimation. Secondly, to increase the convergence speed, the ASTSMO is extended with a linear correction term, where an extra proportionality coefficient is used to adjust the stator current error under dynamic operation. Finally, a novel adaptive law is designed to solve the PMSM’s problems of wide speed change, wide current variation, and inevitable parameters fluctuation, which are caused by the CHC’s complex working environment like frequent load changes and significant temperature variations. In the experimental verification, the position accuracy and dynamic performance of the PMSM are both improved. It is also proved that the proposed strategy can guarantee the stable operation and fast response of the CHC, so as to maintain the reliability and the hydrogen utilization of the hydrogen fuel cell system. Full article

Time-varying lumped disturbance and measurement noise are primary obstacles that restrict the control performance of permanent magnet synchronous motor (PMSM) drives. To tackle these obstacles, an adaptive nonsingular terminal sliding mode (ANTSM) algorithm is combined with augmented recursive sliding mode observer (ARSMO) for PMSM speed regulation system in this paper. Generally, conventional nonsingular terminal sliding mode (NTSM) controller adopts a fixed and conservative control gain to suppress the time-varying disturbance, which will lead to unsatisfactory steady-state performance. Without requiring any information of the time-varying disturbance in advance, a novel barrier function adaptive algorithm is utilized to adjust the gain of NTSM controller online according to the amplitude of disturbance. In addition, the ARSMO is emoloyed to estimate the total disturbance and motor speed simultaneously, thereby alleviating the negative impact of measurement noise and excessive control gain. Comprehensive experimental results verify that the proposed enhanced ANTSM strategy can optimize the dynamic performance of PMSM system without sacrificing its steady-state performance. Full article

Additive manufacturing (AM) via selective laser melting (SLM) is increasingly deployed in aerospace, biomedical, and tooling applications where complex geometries and high performance are required. Yet, process-induced anisotropy and microstructural heterogeneity can strongly affect mechanical and tribological behavior. This study systematically evaluates the combined effects of build orientation (0°, 45°, and 90° relative to the build plate) and post-build heat treatment (as-built, 600 °C, and 860 °C) on the phase constitution, microstructure, hardness, tensile response, and dry sliding wear of SLM-fabricated 316L stainless steel. X-ray diffraction indicated a fully austenitic (γ-fcc) structure without detectable secondary phases across all conditions. Orientation-dependent substructures were observed: ~1 µm equiaxed cellular features at 0°, finer 0.3–0.5 µm cells at 45°, and 1–2 µm elongated features at 90°. Microhardness varied with orientation; relative to 0°, 45° specimens were ~15 HV higher, whereas 90° specimens were ~10 HV lower. Heat treatment at 600 °C promoted refinement and recovery of the cellular network, most pronounced in the 45° orientation, while treatment at 860 °C largely erased melt pool boundary contrast, producing a more homogeneous particle-like microstructure. Tensile fractography revealed dimpled rupture in all cases; the 90° orientation showed finer dimples and lower hardness, consistent with a ductile failure mode under reduced constraint. Dry sliding wear tests identified adhesive wear, intensified by the build-up of transferred fragments, as the dominant mechanism in both as-built and 600 °C conditions. Changes to melt pool morphology after 860 °C heat treatment correlated with altered wear track widths, with the 0° condition showing a notable narrowing relative to the 600 °C state. These results highlight processing pathways for tailoring anisotropy, strength–ductility balance, and wear resistance in SLM 316L. Full article

Electro-hydraulic proportional multi-way valves are widely used in construction machinery and equipment, and their performance directly affects the operation performance of construction machinery and equipment. In this paper, an electro-hydraulic proportional multi-way valve was taken as the research object, and the precise control of the position of the spool of electro-hydraulic proportional multi-way valves under multi-source disturbances was studied. A mathematical model of the electro-hydraulic proportional multi-way valve was established to analyze the influence of hardware controller parameters on the control current. A proportional multi-way valve expansion state observer was established to observe the changes in internal and external multi-source disturbances, and a sliding mode controller was used to compensate for the influence of these disturbances on the position control accuracy of the valve spool of proportional multi-way valves. Compared with the PID control method, the results show that, when using the control method proposed in this paper, the reduction in the step response time and improvement in pressure control accuracy for the pilot proportional reducing pressure valve were maximally 44.4% and 0.61%, respectively; the reduction in the step response time and improvement in control accuracy for the spool of the pilot proportional multi-way valve were maximally 69.48% and 61.74%, respectively. The research results in this paper can help to improve the performance and multi-condition adaptability of electro-hydraulic proportional multi-way valves. Full article

Model predictive control (MPC) is significantly affected by parameter mismatch in inverter applications, whereas model-free predictive control (MFPC) avoids parameter dependence through the ultra-local model (ULM). However, the traditional MFPC based on the algebraic method needs to store historical data for multiple cycles, which results in a sluggish dynamic response. To address the above problems, this paper proposes a model-free predictive control method based on the ultra-local model and an adaptive super-twisting sliding mode observer (ASTSMO). Firstly, the effect of parameter mismatch on the current prediction error of conventional MPC is analyzed through theoretical analysis, and a first-order ultra-local model of the inverter is established to enhance robustness against parameter variations. Secondly, a super-twisting sliding mode observer with adaptive gain is designed to estimate the unknown dynamic terms in the ultra-local model in real time. Finally, the superiority of the proposed method is verified through comparative validation against conventional MPC and the algebraic-based MFPC. Simulation results demonstrate that the proposed method can significantly enhance robustness against parameter variations and shorten the settling time during dynamic transients. Full article

To improve the dynamic response and disturbance rejection performance of a permanent magnet synchronous motor (PMSM) speed control system, this paper designs a speed control strategy of PMSM based on super-twisting sliding mode corrected differential linear active disturbance rejection (STSM-CDLADRC). First, the speed loop model of a permanent magnet synchronous motor based on traditional LADRC is established. Second, the observer of LADRC is reconstructed according to the principle of error control, and the differential linear extended state observer (DLESO) is obtained. Then, to solve the observation hysteresis problem existing in the DLESO, the phase lead correction unit is introduced, and a corrected DLESO is designed (CDLESO); on this basis, the feedback rate in LADRC is also improved by using the super-twisting sliding mode control algorithm to design the super-twisting sliding mode linear state error feedback rate (STSM-LSEF), which improves the dynamic response performance of the system. Finally, the effectiveness and feasibility of the designed control strategy are verified by MATLAB/Simulink simulation and an experimental platform, and the results show that in the speed control system of the PMSM, the strategy effectively improves the dynamic response performance and anti-disturbance performance of the system. Full article

Wheel slipping during trajectory tracking presents significant challenges for wheeled mobile robots (WMRs), degrading accuracy and stability on low-friction or dynamic terrain. Effective control requires addressing unknown slipping parameters while balancing tracking precision and energy efficiency. To address this challenge, a control framework integrating a sliding mode observer (SMO), an improved particle swarm optimization (PSO) algorithm, and a linear quadratic regulator (LQR) is proposed. First, a dynamic model incorporating longitudinal slipping is established. Second, an SMO is designed to estimate the slipping ratio in real-time, with chattering suppressed using a low-pass filter. Finally, an improved PSO algorithm featuring a nonlinear cosine-decreasing inertia weight strategy optimizes the LQR weighting matrices (Q/R) online to both minimize tracking errors and control energy consumption. Simulations including both circular and sine wave trajectories demonstrate that the SMO achieves rapid and accurate slipping ratio estimation, while the PSO-optimized LQR significantly enhances tracking accuracy, achieves smoother control inputs, and maintains stability under varying slipping conditions. Full article

The increasing power demand in substations and the advancement of smart-grid technology point to optical voltage sensors (OVSs) based on the Pockels effect as an attractive solution to replace traditional coil instrument transformers, due to their advantageous characteristics of lower cost and installation space, absence of explosion risks, as well as nonlinear effects such as magnetic hysteresis. Regarding the measurement, our OVS presents excellent linearity, 3 kHz bandwidth, and high input impedance. The primary contribution of this paper is to demonstrate, for the first time, the efficiency of a versatile nonlinear digital controller, based on sliding mode theory, for the optical phase demodulation of an OVS. A simple proportional-integral feedback control is employed to prevent signal fading and generate the two quadrature signals required by the observer, which includes the nonlinear digital controller. Experimental results, for 60 Hz sinusoidal voltages with amplitudes exceeding the half-wave voltage of the OVS, prove that peak-to-peak relative errors remain below 0.8%, while total harmonic distortion (THD) relative errors are under 1.5% when compared to a commercial high-voltage probe used as a reference. These results confirm compliance with Class 1.0 of the UNE-EN 60044-7 standard and show strong potential for applications in power quality measurements. Full article

Aiming at the trajectory tracking control problem of wheeled mobile robots under unknown slip ratio conditions, this paper designs a trajectory tracking controller based on an improved rapid variable power reaching law and a sliding mode observer. First, a kinematic model of the wheeled mobile robot is established, explicitly considering the influence of slip ratio. Then, a sliding mode observer is developed for online estimation of the slip ratio, addressing the difficulty of direct slip ratio measurement. On this basis, a trajectory tracking controller is designed based on the improved rapid variable power reaching law, enabling fast tracking of multiple complex trajectories under slip conditions. Simulation and experimental results show that the proposed trajectory tracking controller not only effectively eliminates the influence of unknown slip disturbances on trajectory tracking, improving smoothness and tracking accuracy but also greatly accelerates the convergence process. The shortest convergence time is only 20.56% of that achieved by a fuzzy PID trajectory tracking controller and 61.43% of that achieved by a rapid double power reaching law trajectory tracking controller with a sliding mode observer. Full article

This paper focuses on enhancing master cylinder pressure control in pressure-sensorless Electro-Hydraulic Brake (EHB) systems. A novel control strategy is developed, integrating a Piecewise Sliding Mode Controller (Piecewise-SMC) with an Extended Sliding Mode Observer (ESMO) based on a newly derived pressure–position–velocity model that accounts for rack position and velocity effects. To handle external disturbances and parameter uncertainties, the ESMO provides accurate pressure estimation. The nonlinear EHB model is approximated piecewise linearly to facilitate controller design. The proposed Piecewise-SMC regulates motor torque to achieve precise pressure tracking. Experimental validation under step-change braking conditions demonstrates that the Piecewise-SMC reduces response time by 31.8%, overshoot by 35.8%, and tracking root mean square error by 9.6% compared to traditional SMC, confirming its effectiveness and robustness for pressure-sensorless EHB applications. Full article

In this paper, we address the problem of jerk and disturbance suppression during mode transitions in power-split hybrid electric vehicles. First, a transient switching model of the PS-HEV is developed. Next, the mechanisms underlying shock generation and the influence of disturbances on transition smoothness are analyzed. Based on this, a fixed-time dynamic coordinated control strategy is proposed, comprising a novel sliding mode control law and a fixed-time extended state observer. The proposed fixed-time sliding mode control law is independent of initial state values and ensures superior convergence performance. Meanwhile, the fixed-time extended state observer enables real-time estimation of external disturbances, thereby reducing the conservatism of the control law. Finally, simulation and hardware-in-the-loop results demonstrate that the proposed strategy markedly improves mode transition performance under various disturbance scenarios. This work provides a new perspective on hybrid mode transition control and effectively enhances transition smoothness. Full article

A key trade-off persists in the control of permanent magnet synchronous motors (PMSMs): achieving fast finite-time convergence often exacerbates control chattering, while conventional chattering-suppression methods can compromise the system’s dynamic response. The existing literature often addresses these challenges in isolation. The core original contribution of this research lies in proposing a novel robust fuzzy adaptive control scheme that effectively resolves this trade-off through a synergistic design. The contributions are as follows: (1) A novel reaching law is formulated to significantly accelerate error convergence, achieving finite-time stability and improving upon conventional reaching law designs. (2) A super-twisting sliding mode observer is integrated into the control loop, providing accurate real-time estimation of load torque disturbances, which is used for feedforward compensation to drastically improve the system’s disturbance rejection capability. (3) A fuzzy adaptive mechanism is developed to dynamically tune key gains in the sliding mode law. This approach effectively suppresses chattering without sacrificing response speed, enhancing system robustness. (4) The stability and convergence of the proposed controller are rigorously analyzed. Simulations, comparing the proposed method with conventional adaptive sliding mode control (ASMC), demonstrate its marked superiority in control accuracy, transient behavior, and disturbance rejection. This work provides an integrated solution that balances rapidity and smoothness for high-performance motor control, offering significant theoretical and engineering value. Full article