Search Results (264)

To address the robustness limitations of three-vector model predictive current control (TV-MPCC) in permanent magnet synchronous motor (PMSM) drives under parameter variations and external disturbances, this paper proposes an improved sliding mode observer (SMO) based on a novel dual power-rate reaching law combined with a hyperbolic tangent function (PTHSMO) for back-EMF estimation and feedforward compensation. The proposed reaching law integrates a terminal attractor term and a nonlinear power-rate term to achieve fast convergence, while the tanh-based switching term continuously approximates the sign function to suppress chattering without requiring a downstream low-pass filter. The estimated back-EMF, which encapsulates the combined effect of parameter mismatch and actual back-EMF, is fed forward into the TV-MPCC prediction model to actively compensate for residual disturbances (denoted PTHESMO). The stability of the observer is verified via the Lyapunov method. Compared with the traditional SMO-based TV-MPCC, the proposed method reduces startup overshoot by approximately 46%, decreases speed recovery time under a 0.3 Nm load disturbance from 46.2 ms to 24.5 ms, and reduces rotor position error from 0.1358 rad to 0.1266 rad, providing an effective solution for high-performance sensorless PMSM drive control. Full article

To address the issues of sluggish dynamic response, significant steady-state fluctuations, and poor disturbance rejection associated with traditional proportional–integral (PI) and conventional speed control methods, a novel sensorless sliding-mode speed control strategy for permanent magnet synchronous motors (PMSMs) based on the super-twisting algorithm (STA) is proposed. First, an advanced sliding-mode speed controller is designed by integrating an integral nonsingular fast terminal sliding-mode surface with the STA, thereby enhancing the dynamic response and transient stability of the PMSM under speed variations. Subsequently, to mitigate inherent sliding-mode chattering, a novel load torque observer is developed. This observer continuously feeds forward real-time load estimates to the speed controller, which substantially improves the system’s robustness against external disturbances. Furthermore, to eliminate the reliance on mechanical sensors and ensure reliable operation across diverse scenarios, an improved sliding-mode observer (SMO) incorporating the STA is utilized to achieve more precise rotor position and speed estimation. Finally, an experimental platform is established to conduct comprehensive variable-speed and variable-load tests on the PMSM. Experimental results demonstrate that the proposed method improves the dynamic response and disturbance immunity of the PMSM by 58.33% and 71.75%, respectively, while reducing steady-state fluctuations by 33.33%. These results demonstrate the effectiveness of the proposed sensorless sliding-mode control strategy and show improved speed regulation performance for PMSM drives. Full article

Traditional permanent magnet synchronous motor (PMSM) control systems rely on mechanical position sensors for high-precision rotor position and speed information, which increases hardware complexity, raises system cost, reduces reliability, and limits adaptability to harsh environments. To overcome the above limitations, this paper proposes a novel high-performance sensorless speed control strategy for PMSMs, which is constructed based on a non-singular terminal sliding mode observer (NTSMO) and a non-singular terminal sliding mode controller (NTSMC). First, an improved fast power reaching law (IFPRL) is proposed, which consists of a variable exponential reaching term and a power reaching term. Specifically, the gain of the exponential reaching term is dynamically adjusted by the absolute value of the sliding mode switching function, enabling the reaching law to operate in two different modes throughout the entire convergence process of the system state. Moreover, the introduction of scaling coefficient c compensates for the performance degradation caused by variations in the range of sliding mode surfaces (SMSs) in different systems. The proposed IFPRL not only effectively mitigates the inherent chattering issue, it also expedites the rate at which the system state converges to its SMS. On this basis, both the NTSMO for rotor position observation and the NTSMC for speed closed-loop control are designed by embedding the proposed IFPRL into the framework of non-singular terminal sliding mode control theory. Finally, the effectiveness of the proposed method is validated through numerical simulations and experimental tests. Experimental results demonstrate that the proposed IFPRL-based NTSMC + NTSMO scheme reduces the root mean square error (RMSE) of speed control by 2.7% relative to the traditional SMC + SMO method. The proposed method realizes reliable sensorless speed control for PMSMs and exhibits superior dynamic response, higher control accuracy, and stronger robustness against disturbances. Full article

High-performance control of surface-mounted permanent magnet synchronous motors (SPMSMs) is critical for unmanned aerial vehicle (UAV) rotor servo systems, which demand fast dynamic response, high steady-state accuracy, and strong robustness against complex disturbances. However, conventional sliding mode control (SMC) methods often suffer from inherent issues like integral windup, persistent chattering, and sensitivity to parameter variations, limiting their effectiveness in such challenging applications. To address these limitations, this paper proposes a novel composite control strategy. The method integrates an improved terminal integral sliding mode controller (ITISMC) with an adaptive super-twisting reaching law (ADSTA) and a terminal integral sliding mode observer (TISMO). The key innovations include: (1) a redesigned sliding surface incorporating a smooth nonlinear function to suppress chattering and a variable-gain integral term to mitigate integral windup; (2) an adaptive reaching law that dynamically adjusts its gains based on the system state to balance convergence speed and chattering suppression; and (3) a disturbance observer that provides real-time estimation and feedforward compensation of total disturbances, significantly enhancing robustness. The proposed ITISMC-ADSTA-TISMO strategy was implemented and validated on a TMS320F28379D DSP-based experimental platform. Comparative results demonstrate its superiority over benchmark methods (e.g., SMC-STA). Key achievements include a rapid no-load startup time of 0.45 s, high steady-state precision with speed fluctuations suppressed to only 3 rpm, and superior disturbance rejection capability under sudden load changes, sinusoidal disturbances, and parameter perturbations. The method also yields favorable q-axis current response. These results confirm that the proposed strategy offers a high-performance, practical solution for advanced UAV servo control systems. Full article

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

An emotional neural network-based global predefined-time sliding mode control (ENN-GPTSMC) method is proposed for an uncertain hybrid mechanism. To estimate and compensate for the lumped uncertainty including discontinuous friction, an emotional neural network is developed. Simultaneously, a predefined-time terminal sliding mode control (PTTSMC) uses the estimation value. The adjustable predefined-time performance parameters are then incorporated into the PTTSMC law to extend its attractiveness for the system states to the global domain, thereby solving the limitation of the existing PTTSMC that can only locally achieve the predefined-time convergence of the system states during the reaching phase. The fast convergence of system states is subsequently achieved by embedding an integer-power linear term and its derivative into the sliding manifold and PTTSMC law, respectively. Based on these, an ENN-GPTSMC algorithm is designed. Furthermore, the saturation function of a dynamic boundary layer with an adjustable thickness is designed to avoid the singularity of ENN-GPTSMC, thereby achieving no-singularity fast global predefined-time convergence of the system. Theoretical analysis shows the Lyapunov stability of the system. Finally, simulation and prototype experiments are used to verify the effectiveness of the proposed method. Full article

To address the robustness degradation of intelligent vehicle fleet longitudinal control systems caused by the coexistence of disturbances and time-delay, a longitudinal finite-time control strategy based on a predictive finite-time extended state observer (PFTESO) is proposed. First, a finite-time extended state observer (FTESO) is designed to estimate system disturbances. To address the observer input asynchrony induced by time-delay, an improved Smith predictor is integrated into the FTESO to construct the PFTESO, thereby improving disturbance observation accuracy under delayed conditions. Meanwhile, a proportional–integral (PI) compensation controller is introduced based on the estimation error to further enhance control accuracy. Subsequently, a global fast integral terminal sliding mode controller (GFITSMC) is developed based on the PFTESO to improve the robustness and finite-time convergence performance of the intelligent vehicle fleet system under disturbances and time-delay. Finally, comparative simulation studies under different operating conditions are conducted to evaluate the effectiveness of the proposed strategy. Simulation results demonstrate that the proposed PFTESO effectively improves state observation accuracy under delayed conditions, where the RMSE values of z₁ and z₂ are reduced from 0.082 and 0.214 to 0.021 and 0.067, respectively. In addition, compared with conventional sliding mode control strategies, the proposed FTESO-GFITSMC reduces the peak acceleration chattering from ±0.23 m/s² to 0.03 m/s² while achieving a finite-time convergence time of 13 s. The proposed method exhibits superior robustness, faster convergence performance, and smoother acceleration response for an intelligent vehicle fleet under disturbances and delayed conditions. Full article

Deploying unmanned aerial vehicles (UAVs) cooperatively with legged robots for disaster response and inspection requires autonomous docking on miniature walking platforms. This study addresses the problem of landing a foldable quadrotor onto the back of a trotting wheel-legged robot ($300\times 180$ mm) and subsequently taking off while carrying it as a payload. Four tightly coupled challenges distinguish this task from conventional mobile-platform landing: (i) an extremely small landing surface, (ii) gait-induced periodic vibrations at $2.5$ Hz, (iii) continuous platform translation at $0.3$–$0.8$ m/s, and (iv) surface docking that requires simultaneous position and attitude matching rather than mere point tracking. The proposed framework comprises four components: (1) a novel single-servo crank-rocker folding mechanism that reduces the folded body footprint by 48.5% and the maximum linear dimension from 590 mm to 309 mm (↓47.6%) compared with the prior dual-servo design; (2) a staged Continuous Fast Nonsingular Terminal Sliding Mode (CFNTSM) controller combined with a Gait-Frequency-Aware Finite-time Extended Observer (GFA-FEO); (3) a Feature-wise Linear Modulation Soft Actor-Critic (FiLM-SAC) residual reinforcement-learning policy conditioned on physical states and mission phase, with an adaptive trust weight $\lambda \left(t\right)$; and (4) a payload-adaptive takeoff strategy with parameter hot-switching to handle the twofold mass increase. Extensive Monte Carlo simulations and ablation studies across three experiment groups demonstrate that the proposed hierarchical framework achieves sub-centimetre (<10 mm) position accuracy and <3° attitude matching on a walking platform. Quantitatively, the full method reduces docking RMSE by 42% relative to the model-based CFNTSM + GFA-FEO controller without residual RL (4.2 vs. 7.2 mm) and reduces post-lock takeoff RMSE by 63% through FEO hot-switching (16.2 vs. 44.2 mm). Full article

In this paper, a novel anti-windup prescribed performance terminal sliding mode control method is proposed for the fixed-time tracking problem of a nonholonomic constrained mobile deicing manipulator system with model uncertainty and external disturbance. Firstly, a fixed-time preset performance function related to the initial error is proposed to constrain and transform the tracking error, so as to ensure that the tracking error of the system converges in a fixed time and has good transient and steady-state performance. Secondly, in order to accelerate the convergence to the equilibrium state, a fast terminal sliding mode surface with preset performance tracking error and a new fixed time reaching rate are constructed. By using Lyapunov analysis, the global fixed-time convergence of the scheme is theoretically verified. The control method is compared with the FTSMC method through simulation experiments, and the effectiveness of the designed control method is further verified. Full article

Aiming to improve the robustness of two-phase buck converters powering DC bus of permanent magnet synchronous motor drives, this article presents a novel voltage regulation scheme. The proposed scheme comprises a three-switching-surface nonsingular fast terminal sliding mode controller (TSS-NFTSMC) for output voltage regulation and a current balancing controller to equalize the inductor currents. Due to the fast terminal sliding mode surface, the output voltage error converges more rapidly both when far from zero and when approaching zero. The phase plane is split into four regions by three independent switching surfaces. Based on the region where the sliding variable resides, the TSS-NFTSMC can directly decide the number of enabled high-side switches, which helps suppress internal disturbances effectively. The stability and convergence of the presented control system are verified via Lyapunov stability analysis. The convergence property of TSS-NFTSMC is independent of the current controller. Both simulation and experimental results demonstrate that the proposed control strategy achieves satisfactory dynamic response and strong disturbance rejection capability. Full article

Cable-driven manipulators have emerged as a compelling alternative to traditional manipulators (driven by either electrical, hydraulic, or pneumatic motors), especially for operations in constrained and complex environments. Despite offering many advantages, they still pose significant control challenges. Therefore, this paper presents a novel position tracking control framework for an n-DOF cable-driven manipulator subject to lumped mismatched uncertainties arising from unknown dynamic errors and external disturbances. The proposed approach is built upon non-singular fast terminal sliding mode control (NFTSMC), which provides robustness, high-precision tracking, fast finite-time convergence, chattering-free torque input, and complete elimination of singularity issues. To further enhance control performance, an extended state observer (ESO) is incorporated to accurately estimate unmeasured states and suppress lumped uncertainties. The stability of the closed-loop system under the proposed method is rigorously proven by the Lyapunov theorem. Finally, the superiority of the proposed method over existing controllers is demonstrated by comparative simulations to highlight its potential for practical implementation in complex robotic environments. Full article

This paper proposes a finite-time target tracking control for multi-rotor unmanned aerial vehicles (UAVs) based on a vision-inertial-stabilized platform. To address the challenge of stable and accurate moving target tracking, the sliding mode control (SMC) technique is used to overcome limitations of conventional control algorithms, such as poor robustness and slow convergence speed. First, by computing the pixel deviation between the target and the image center, a kinematic model of the tracking target is established. Then, by introducing homogeneous system theory into the sliding mode surface design, a non-singular fast integral terminal sliding mode control (NFITSMC) is designed for target tracking via regulating the rotational angular acceleration of dual actuators in the vision inertial stabilized platform, thereby driving the pixel deviation to converge to zero in a finite time. Strict theoretical analysis is given to prove the finite-time stability and robustness of the closed-loop control system. Furthermore, simulation results demonstrate that the proposed method maintains higher tracking accuracy than SMC, ISMC, and TSMC. Full article

To address the deteriorated control performance of permanent magnet synchronous motor (PMSM) drive systems for new energy vehicles (NEVs) under complex conditions caused by multi-source disturbances (internal parameter perturbations and external load mutations), this paper proposes an improved terminal integral sliding mode control (ITISMC-ADERL) strategy integrating a piecewise adaptive terminal integral sliding mode surface and an ADERL. The proposed sliding mode surface adopts interval-adaptive switching between high- and low-order power terms, completely eliminating singularity and integral saturation defects of traditional terminal sliding mode control while ensuring fast convergence, and achieving an optimal structural balance between convergence speed and chattering suppression. The state-dependent ADERL leverages the synergy of error-sliding variable coupled dynamic gain adjustment and variable exponential power compensation, realizing dual-mode adaptive switching of “strong driving for fast approaching far from the sliding surface, weak gain for smooth regulation near the sliding surface”, which significantly improves control accuracy and anti-disturbance robustness. The finite-time convergence of the closed-loop system is rigorously proved via Lyapunov stability theory. Full-operating-condition comparative tests on a TMS320F28379D DSP platform show that the proposed strategy outperforms SMC-ERL, ISMC-ERL and ITISMC-ERL in all test scenarios (no-load startup, acceleration/deceleration, sudden load changes, flux linkage perturbation), meeting the requirements of high-performance NEV drive systems and possessing important engineering application potential. Full article

This paper proposes a novel adaptive sliding mode control strategy for bionic aerial manipulators performing canopy-sampling tasks. Specifically, an adaptive neural barrier function-based fast terminal sliding mode control (BFASMC-NN) scheme is developed to address the joint-space trajectory tracking problem by integrating fast continuous nonsingular terminal sliding mode control (FNTSMC), neural networks (NNs), and barrier functions (BFs). The aerial manipulator is modeled as a rootless system, and its kinematic and dynamic characteristics are analyzed separately. Radial basis function neural networks (RBF-NNs) are introduced to approximate lumped disturbances, while BFs are incorporated to mitigate the effects of joint input saturation. Meanwhile, FNTSMC is employed to guarantee finite-time convergence of the system states. The stability of the closed-loop system is rigorously proven based on Lyapunov stability theory. Two simulation studies are conducted to validate the proposed method, and the results demonstrate that it achieves stronger disturbance rejection capability, faster convergence, and higher tracking accuracy than existing approaches. Full article

Permanent magnet synchronous motor (PMSM)-driven position servo systems in high-speed flight vehicles face severe challenges from extreme thermal environments, which induce significant parameter variations up to 25% (e.g., motor torque constant) and complex multi-scale disturbances. This paper proposes a novel adaptive robust control strategy integrating three key components: (1) an ultra-local model formulation motivated by physically consistent thermal effect analysis of electromagnetic, mechanical, and tribological parameters; (2) a dual-layer disturbance observer architecture comprising a third-order finite-time convergent extended state observer (FTCESO) for fast-varying disturbances and a σ-modification adaptive estimator for slow-varying thermal drifts; and (3) a global nonlinear integral terminal sliding mode controller with a cycloidal reaching law. Stability analysis based on homogeneous system theory and Lyapunov methods establishes practical finite-time convergence with explicit bounds. The experimental results on a TMS320F28335-based servo platform demonstrate that the proposed method reduces the maximum position deviation by 83–94% compared to PID, LADRC, and conventional SMC controllers under the tested disturbance conditions, achieving settling time reductions exceeding 90%. Under combined thermal drift and external loading, the proposed approach limits the maximum tracking error to below 0.45° while maintaining a steady-state error under 0.08°. Full article