Search Results (69)

Unmanned airships are highly sensitive to parametric uncertainty, persistent wind disturbances, and sensor noise, all of which compromise reliable path-following. Classical control schemes often suffer from chattering and fail to handle index discontinuities on closed-loop paths due to the lack of mechanisms and cannot simultaneously provide formal guarantees on state constraint satisfaction. We address these challenges by developing a unified, constraint-aware guidance and control framework for path-following in uncertain environments. The architecture integrates an extended state observer (ESO) to estimate and compensate lumped disturbances, a barrier Lyapunov function (BLF) to enforce state constraints on tracking errors, and a super-twisting terminal sliding-mode (ST-TSMC) control law to achieve finite-time convergence with continuous, low-chatter control inputs. A constructive Lyapunov-based synthesis is presented to derive the control law and to prove that all tracking errors remain within prescribed error bounds. At the guidance level, a nonlinear curvature-aware line-of-sight (CALOS) strategy with an index-increment mechanism mitigates jump phenomena at loop-closure and segment-transition points on closed yet discontinuous paths. The overall framework is evaluated against representative baseline methods under combined wind and parametric perturbations. Numerical results indicate improved path-following accuracy, smoother control signals, and strict enforcement of state constraints, yielding a disturbance-resilient path-following solution for the cruise of an unmanned airship. Full article

This study presents a comprehensive performance analysis of four different control strategies, Proportional–Integral (PI), classical Sliding Mode Control (SMC), Super-Twisting SMC (ST-SMC), and Exponential Reaching Law SMC (ERL-SMC), applied to the speed regulation of a Hall-effect sensored Brushless DC (BLDC) motor. A mathematically detailed BLDC motor model, three-phase inverter structure with safe commutation logic, and a high-frequency PWM switching scheme were implemented in the MATLAB/Simulink-2024a environment to provide a realistic simulation framework. The control strategies were evaluated under multiple test scenarios, including variations in supply voltage, mechanical load disturbances, reference speed transitions, and steady-state operation. The comparative results reveal that the classical SMC and PI controllers suffer from significant oscillations, overshoot, and limited disturbance rejection capability, especially during voltage and load transients. The ST-SMC algorithm improves robustness and reduces the chattering effect inherent to first-order SMC but still exhibits noticeable oscillations near the sliding surface. In contrast, the proposed ERL-SMC controller demonstrates superior performance across all scenarios, achieving the lowest steady-state ripple, the shortest settling time, and the most stable transition response while significantly mitigating chattering. These results indicate that ERL-SMC is the most effective and reliable control strategy among the evaluated methods for BLDC speed regulation, which requires high dynamic response and disturbance robustness. The findings of this study contribute to the advancement of SMC-based BLDC motor control, providing a solid foundation for future research that integrates observer-based schemes, adaptive tuning, or real-time hardware implementation. Full article

The dynamic model of a spatial flexible manipulator is challenging to establish accurately and is susceptible to disturbances from uncertainties, which negatively impact system control. To mitigate the effects of uncertainties and improve control precision, this paper develops the dynamic model of a spatial flexible manipulator system using the Lagrange principle and the assumed mode method. Additionally, to address the chattering issue in sliding mode control, a super-twisting algorithm sliding mode control strategy is proposed, which utilizes an RBF neural network to compensate for system uncertainties. By incorporating the concept of higher-order sliding mode, the super-twisting algorithm sliding mode is integrated with non-singular terminal sliding mode to design the sliding surface and control law, ensuring the stable and rapid convergence of the system state while reducing chattering. The simulation results demonstrate that the proposed strategy reduces fluctuations in rotation angle and angular velocity errors at both the input and output ends, enhances trajectory tracking performance, and achieves effective chattering suppression. Full article

The electrification of agricultural machinery has become an important trend. Active Disturbance Rejection Control (ADRC) shows considerable potential in agricultural motor control due to its low model dependence and strong anti-disturbance capability. However, the Extended State Observer (ESO) of traditional ADRC is limited by bandwidth, making it difficult to effectively capture high-frequency impact disturbances such as torque fluctuations during straw cutting, which results in reduced efficiency and increased energy consumption. To address this, this paper proposes an improved ADRC scheme: designing a Super-Twisting Extended State Observer (STESO) by integrating Super-Twisting technology to enhance disturbance observation capability; incorporating a Quasi-Proportional Resonant (QPR) controller into the Error Feedback Control Law (SEF) to compensate for the shortcoming of disturbance suppression beyond ESO bandwidth; and proposing a decoupling strategy to reduce the difficulty of parameter tuning and optimize control performance. Simulations and experiments on the Permanent Magnet Synchronous Motor (PMSM) of an automatic seeder demonstrate that the proposed method can effectively suppress various disturbances, reduce speed regulation errors, and not deteriorate dynamic responses. Full article

This study addresses robust trajectory tracking for quadrotor unmanned aerial vehicles (QUAVs) under partial state measurements and bounded external disturbances. To this end, a control framework is introduced that integrates backstepping sliding mode control (BSMC) with a super-twisting observer (STO). In this scheme, only position and attitude are directly measured while the STO reconstructs the linear and angular velocities in real time. The estimated states are then fed into the control law, enabling accurate trajectory tracking and robust performance without full-state feedback or explicit disturbance compensation. The approach is validated through three simulation scenarios: nominal full-state feedback, observer-based control without disturbances, and observer-based control under bounded time-varying perturbations. Quantitative metrics confirm consistent tracking accuracy and closed-loop stability across all scenarios. These results demonstrate the effectiveness of the integrated BSMC–STO framework for QUAV operations in sensor-limited and disturbance-prone environments. Full article

This paper introduces a novel sensorless speed control strategy for squirrel-cage induction motors, which ensures robust operation in the presence of external disturbances by applying the state feedback technique. Based on the induction motor model, the speed controller is synthesized by defining a sliding variable that is driven to zero through the supertwisting control law, ensuring the stabilization of the tracking error. The time derivative of the error variable is estimated using a robust differentiator based on the sliding-mode twisting algorithm, thereby eliminating the need to estimate the load torque. A robust observer is employed to estimate the rotor speed and flux linkages simultaneously. The convergence of the estimated rotor flux linkages is enforced through a discontinuous first-order sliding-mode input, while the convergence of the rotor speed estimate is attained via a quasi-continuous super-twisting sliding-mode input. In the proposed model, the inductance parameters are determined from the magnetizing inductance and the leakage inductances of the stator and rotor. A procedure is also presented for adjusting the stator resistance and leakage inductances, taking into account the squirrel-cage rotor type and the skin effect in alternating current conduction. The performance of the sensorless speed control system under variations in load torque and reference speed is validated through experimental testing. The rotor speed estimation provided by the robust observer is accurate. The reference speed tracking control, evaluated using a 1600–1700 rpm pulse train phase-shifted by 4 s with respect to a 0–0.5 N·m pulse train, demonstrates high precision. 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

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

This study proposes a hierarchical composite adaptive sliding-mode control strategy to address the strong nonlinear dynamics of a hexarotor Unmanned Aerial Vehicle (UAV) and the external disturbances encountered during flight. First, within the position-control loop, a Terminal Sliding Mode Control (TSMC) is designed to guarantee finite-time convergence of the system states, thereby significantly improving the UAV’s rapid response to complex trajectories. Concurrently, an online Adaptive rates mechanism is introduced to estimate and compensate unknown disturbances and modeling uncertainties in real time, further enhancing disturbance rejection. In the attitude-control loop, a Super-twisting Sliding Mode Control (STSMC) method is employed, where an Adaptive rate law dynamically adjusts the sliding gain to prevent overestimation and high-frequency chattering, while ensuring fast convergence and smooth response. To comprehensively validate the feasibility and superiority of the proposed scheme, a representative helical trajectory-tracking experiment was conducted and systematically compared, via simulation, against conventional control methods. Experimental results demonstrate that the proposed approach achieves stable control within 0.15 s, with maximum position and attitude tracking errors of 0.05 m and 0.15°, respectively. Moreover, it exhibits enhanced robustness and adaptability to external disturbances and parameter uncertainties, effectively improving the motion-control performance of hexacopter UAVs in complex missions. Full article

In response to the limitations of suboptimal control accuracy, compromised synchronization capability, and reduced stability inherent in PID control for conventional shaftless multi-permanent magnet synchronous motor drive systems, this article establishes a three-motor synchronous control system model for a shaftless printing system. On this basis, the speed loop adopts a sliding mode controller (NSMC) based on a new approach law, and the current loop adopts an improved super spiral structure. At the same time, the compensator of the deviation coupling control structure (NDCS) is optimized by weighted arithmetic mean. Finally, comparative simulation experiments were conducted on the system model using various algorithms. The results show that the deviation coupling control structure based on improved sliding mode control has better anti-interference ability, control accuracy, and synchronization in the synchronous control strategy of a multi-permanent magnet motor drive in a shaftless printing system, which is conducive to the safe and stable operation of shaftless printing systems under multiple working conditions. Full article

Piezoelectric actuators are commonly used in high precision, micro-displacement applications. However, nonlinear phenomena, like hysteresis, may reduce their performance. This article compares several control approaches—based on the combination of sliding mode control and artificial neural networks—for coping with these nonlinearities and improving actuator positioning accuracy and robustness. In particular, it discusses the application of diverse order sliding mode control techniques, such as conventional, twisting algorithms, super-twisting algorithms, and the prescribed convergence law, in combination with artificial neural networks. Moreover, it validates experimentally, with a commercial piezoelectric actuator, the application of these control structures using a dSPACE 1104 controller board. Finally, it evaluates the computational time consumption for the control strategies presented. This work intends to guide the designers of PEA commercial applications to select the best control algorithm and identify the hardware requirements. Full article

In this article, a novel finite-time convergent three-dimensional terminal sliding mode guidance law is proposed for intercepting maneuvering targets in three-dimensional space with terminal angle constraints. The proposed guidance law introduces a novel generalized super-twisting extended state observer (GSTESO) to estimate the maneuvering target’s acceleration and lumped disturbances, enabling quicker convergence to the true values and offering better noise tolerance. Moreover, a time-varying function called time base generator (TBG) is introduced in the design of the sliding surface, forming a new terminal sliding mode function that ensures that the line-of-sight (LOS) angle converges within a small neighborhood of the desired value at interception. It also offers good robustness and higher guidance accuracy, effectively avoiding overload saturation in the initial stages of guidance. Simulation results indicate that the proposed TBG-based finite-time terminal sliding mode (TBGFTTSM) guidance law can reduce overload magnitude and ensure continuous and smooth guidance commands, while the performance of the GSTESO is also validated. Full article

This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. This hybrid approach effectively mitigates the inherent chattering issue commonly associated with sliding-mode control while maintaining high levels of control system precision. We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. During the guidance phase, a pre-trained reinforcement learning model is employed to directly map the missile’s state variables to the optimal adaptive parameters, thereby significantly enhancing the guidance performance. Additionally, a generalized super-twisting extended state observer (GSTESO) is introduced for estimating and compensating the lumped uncertainty within the missile guidance system. This method obviates the necessity for prior information about the target’s maneuvers, enabling the proposed guidance law to intercept maneuvering targets with unknown acceleration. The finite-time stability of the closed-loop guidance system is confirmed using the Lyapunov stability criterion. Simulations demonstrate that our proposed guidance law not only meets a wide range of impact angle constraints but also attains higher interception accuracy and faster convergence rate and better overall performance compared to traditional NTSM and the super-twisting NTSM (ST-NTSM) guidance laws, The interception accuracy is less than 0.1 m, and the impact angle error is less than 0.01°. Full article

In this paper, a nonlinear sliding-mode super-twisting reaching law algorithm is designed to address the problem of coupling interference under deception attacks and actuator physical faults in USV formations during cooperative mining operations of a USVs-ROVs system. First, a USV model with attacks and disturbances is established, and a leader–follower formation system is designed. Then, based on the reaching law, the state error dynamic chatter can be effectively solved when it is far away from and reaches the sliding surface; a nonlinear sliding super-twisting reaching law is designed to improve the chatter characteristics of the sliding surface. Furthermore, to solve the problems of low fitting accuracy regarding control anomaly information and the difficulty of fending off signal-data interference attacks, a nonlinear saturation fault-tolerant filtering mechanism and a nonlinear fitting factor are designed. Finally, the stability of the algorithm is verified through Lyapunov theory. Under the same coupling deception probability, the nonlinear sliding-mode super-twisting reaching law algorithm designed in this paper enables the leader ship and each follower ship to reach stability within about 12s, and the formation system maintains its formation while also improving the control accuracy of each individual ship. Full article

An improved super-twisting sliding mode and linear active disturbance rejection control strategy is proposed to improve the dynamic response performance and immunity performance in switched reluctance motor speed control systems. Firstly, the linear extended state observer in linear active disturbance rejection control is improved by using the super-twisting sliding mode (STSM) control algorithm in order to improve the performance of the observer and thus enhance the controller’s immunity to disturbances. Secondly, the STSM control algorithm is used to replace the original linear state error feedback control law to improve the dynamic response performance of the controller, and the sigmoid function is used to replace the sign function in the STSM algorithm to further weaken the inherent chattering of the sliding mode and improve the stability of the system. Finally, the proposed control strategy is verified using the MATLAB/Simulink simulation platform. The simulation results show that the proposed control strategy has a better dynamic response and disturbance immunity performance. Full article