Search Results (172)

This paper presents an adaptive event-triggered nonsingular fast terminal sliding-mode control (AETSMC) framework for quadrotor unmanned aerial vehicles subject to aerodynamic disturbances, actuator loss of effectiveness (LOE) of up to 60%, and intermittent denial-of-service (DoS) attacks. First, a nonsingular fast terminal sliding-mode (NFTSM) surface is constructed using fractional powers of the tracking error rather than fractional-order derivatives. This design ensures finite-time convergence while avoiding the singularity associated with conventional terminal sliding-mode schemes. Second, a smooth positive-semidefinite barrier function (Smooth-PSBF) is incorporated into the adaptive gain law. The resulting law provides only the compensation required to maintain the prescribed bound, thereby limiting gain overestimation and chattering. Third, a dual-mode event-triggering mechanism combines an exponentially decaying threshold with a zero-order hold. A positive lower bound on the inter-event interval is derived from the closed-loop dynamics, which excludes Zeno behaviour. Simulations under matched conditions show that the proposed method reduces the pitch-channel root-mean-square error by 79.4% and the integral squared error by 95.8% relative to the first reproduced baseline. In a separate 15-s communication experiment sampled at 1 kHz, the controller generated 128 transmissions instead of 15,000 periodic updates, corresponding to a 99.15% reduction. These results indicate that the proposed framework can improve fault-tolerant tracking while reducing communication demand under intermittent DoS attacks. Full article

This paper addresses the finite-time global Mittag-Leffler projective synchronization problem for a class of uncertain fractional-order delayed neural networks with heterogeneous fractional orders, parameter uncertainties, and multiple time delays. A novel integral sliding mode control approach is developed by designing a delayed integral sliding manifold and an appropriate robust reaching law, such that the synchronization error trajectories are driven to the sliding surface within finite time. Furthermore, sufficient algebraic conditions are established to guarantee the global Mittag-Leffler stability of the reduced-order error dynamics on the sliding manifold. Under the proposed control scheme, finite-time projective synchronization is achieved in the presence of heterogeneous fractional orders, uncertain parameters, time delays, and nonlinear coupling effects. Finally, a numerical example is provided to demonstrate the validity and effectiveness of the proposed theoretical results. Full article

Focusing on the vertical return mission scenario of reusable launch vehicles, analytical guidance methods commonly adopted in existing research lack effective fuel prediction mechanisms, which severely restricts the mission reliability and fuel economy of vehicle vertical landing, and fails to achieve high-precision velocity constraint control and stable anti-disturbance guidance in the full powered descent and terminal landing process. To address the above problems, this paper proposes a multi-phase integrated guidance framework that integrates predefined-time time-varying fractional-order sliding mode control and fuel consumption forecasting. A fuel consumption prediction model incorporating potential energy factor, kinetic energy factor and interference factor is constructed to realize full-process fuel demand prediction in the trajectory planning stage, and the proposed guidance scheme achieves high-precision and strong anti-disturbance guidance performance while satisfying strict full-stage velocity constraint requirements. Simulation results show that the proposed method can realize stable and accurate vertical soft landing under diverse disturbance conditions with minor fuel prediction errors. This method addresses the limitations of traditional analytical guidance methods in terms of mission reliability and fuel economy, improves the system robustness of vertical recovery missions, and provides an effective technical reference for precise landing guidance of reusable launch vehicles. Full article

To address the motion control challenges of remotely operated vehicles (ROVs) under model uncertainties, external disturbances, and uncertain hydrodynamic parameters, this study proposes a fractional-order super-twisting sliding mode control (FOST-SMC) strategy based on improved active disturbance rejection control (IADRC). The proposed method reduces dependence on accurate dynamic models and enhances disturbance rejection capability by integrating IADRC with FOST-SMC. A sine-function-based nonlinear extended state observer (ESO) was developed to improve lumped disturbance estimation and noise robustness. The proposed ESO reduces the root mean square (RMS) estimation error from 2.226 × 10⁻⁵ to 5.224 × 10⁻⁶, corresponding to a 76.5% reduction compared with the conventional ESO. Lyapunov analysis verified the stability of the closed-loop system. MATLAB/Simulink version R2024a (MathWorks, Natick, MA, USA) simulations based on the Falcon ROV model demonstrated improved tracking performance under step response, sinusoidal tracking, and three-dimensional trajectory tracking with time-varying disturbances and Gaussian white noise. Compared with conventional active disturbance rejection control (ADRC), the proposed controller achieved average RMSE reductions of 87.0%, 57.2%, and 49.4 to 65.4% in different tracking scenarios, respectively. The proposed strategy provides an effective approach for robust ROV motion control in uncertain underwater environments. Full article

This paper investigates the task-space position tracking problem of a redundant manipulator under multiple disturbances. Different from conventional joint-space tracking schemes, the considered task only constrains the end-effector position, leaving redundant degrees of freedom to be exploited for secondary optimization. However, conventional computed torque control is sensitive to dynamic-model mismatch, while integer-order equivalent input disturbance compensation has limited flexibility in balancing disturbance tracking and noise attenuation. To address these limitations, a composite control framework is proposed by integrating task-space position error regulation, null-space redundancy optimization, and a fractional-order equivalent input disturbance compensation (FEIDC) strategy. The task-space controller generates the desired acceleration, which is mapped to the joint acceleration command through a damped pseudoinverse Jacobian, and a null-space term is incorporated to optimize secondary criteria. For the feedback-linearized joint dynamics, the proposed FEIDC introduces a fractional-order filter into the equivalent input disturbance estimation channel, providing an additional order parameter for shaping disturbance attenuation and noise sensitivity. Simulation validation on a UR5e manipulator compares the effectiveness of the proposed method with sliding mode control (SMC), active disturbance rejection control (ADRC) and integer-order equivalent input disturbance compensation strategy (IEIDC). In comparisons with SMC, ADRC, and IEIDC, the proposed FEIDC achieves the lowest joint and Cartesian RMSEs, namely, $7.2863\times {10}^{-4}$ rad and $3.8035\times {10}^{-4}$ m, respectively. Full article

The increasing demand for sustainable and intelligent energy solutions in electric vehicles (EVs) has led to a significant interest in the development of advanced hybrid energy storage systems (HESS) and efficient wireless charging architectures. In this work, a dynamic sliding mode control (DSMC) technique is optimized through a swarming heuristics framework for a battery-ultracapacitor HESS integrated with a wireless power transfer (WPT) system. Leveraging an LCC-S topology, the WPT system enables high-efficiency, contactless energy transfer to the storage modules under varying load and alignment conditions. To address the nonlinearities and parameter uncertainties inherent in such systems, a robust DSMC approach is formulated to ensure smooth system tracking and disturbance rejection. The control design is further refined using a bio-inspired moth–flame optimization algorithm hybridized with gravitational search and fractional-order PSO (MFOGSAPSO)—enhanced with adaptive entropy regulation and fractal-based memory—to dynamically tune the sliding-surface coefficients and switching gains. The proposed methodology is validated through comprehensive simulations in MATLAB/Simulink and a controller hardware-in-the-loop (C-HIL) setup on TI F28379D LaunchPads. Among the three MFO variants, MFOGSAPSO-A achieves the fastest objective function convergence, stabilizing near 685 within 10 iterations and substantially outperforming the optimized PID (715) and Optimized SMC (708). The proposed DSMC attains an overall RMSE of $0.1081$, reducing the tracking error by $60.69\%$ relative to PID and $14.84\%$ relative to SMC, while shortening the settling time to $0.102$ ms against PID ($84.84\%$) and SMC ($23.88\%$) improvements. The C-HIL results closely match the offline simulation waveforms without retuning, confirming superior energy management, improved power sharing between the battery and ultracapacitor, and enhanced overall efficiency of the wireless charging process under realistic embedded execution. Full article

Quadrotor unmanned aerial vehicles (QUAVs) exhibit strongly coupled nonlinear dynamics and are highly sensitive to disturbances and measurement noise, which can significantly degrade trajectory tracking performance and induce chattering in sliding mode-based controllers. In this work, a fractional-order backstepping sliding mode control (FO-BSMC) strategy is proposed for QUAV trajectory tracking. In contrast to existing fractional-order sliding mode approaches, where the fractional operator is typically introduced into the sliding surface or control law, the proposed methodology incorporates fractional-order behavior directly into the QUAV dynamic model through the Caputo definition, while the Grünwald–Letnikov approximation is adopted for numerical implementation. A conventional integer-order BSMC scheme is also developed, and Lyapunov-based stability analyses are presented for both the conventional BSMC and the proposed FO-BSMC formulations. The fractional order is selected using the PSO algorithm. The performance of both controllers is evaluated under external disturbances, perturbed initial conditions, and measurement noise. Monte Carlo simulations are further conducted to assess the sensitivity of the closed-loop system to initialization uncertainties. The simulation results demonstrate that the proposed FO-BSMC achieves lower tracking errors, faster convergence, improved robustness against external disturbances and measurement noise, and smoother control actions with reduced chattering than the conventional BSMC. Full article

The development of fractional-order control has been derived from the mathematical generalization of classical calculus and has become an important tool in the modeling and control of dynamical systems with memory and hereditary effects. In spite of the rapid development of this area of control theory and applications, the overall scientific development, structure, and engineering relevance of fractional-order control remain insufficiently understood. In this paper, we address this problem by combining large-scale bibliometric analysis with representative controller performance studies. A total of 6482 publications indexed in the Web of Science database during the period 2010–2026 are analyzed. The bibliometric results indicate that fractional-order control is an increasingly connected global research field with strong roots in fractional calculus, advanced control theory, and growing interdisciplinary links with applied mathematics, automation, and computer science. To further illustrate controller level behavior, representative simulations are performed on a fractional-order time-delay process and an uncertain nonlinear system. For the fractional-order time-delay process, a well-tuned PID controller is compared with a realizable FOPID controller implemented through Oustaloup recursive approximation. The results show that the FOPID controller improves several performance measures, including overshoot, settling time, control energy, total variation, and sensitivity peak, while the comparison is interpreted as a performance trade-off rather than universal superiority. For the uncertain nonlinear system, fractional-order sliding mode control produces smoother control action and substantially reduces chattering. By combining bibliometric mapping with representative performance evaluation, this paper provides a comprehensive overview of fractional-order control as a globally active and practically relevant discipline in control engineering. Full article

The increasing demand for clean, reliable, and sustainable energy has intensified the need for advanced control strategies in modern wind energy conversion systems. Although conventional backstepping control (BC) offers strong stability and robustness, its performance may deteriorate under parameter uncertainties and dynamic operating conditions, leading to power fluctuations and reduced energy quality. To overcome these challenges, this study proposes an intelligent fuzzy fractional-order BC (FFOBC) strategy for multi-machine wind energy systems. By integrating fuzzy logic with fractional-order calculus into the classical BC framework, the proposed approach enhances adaptability, dynamic response, and robustness against system disturbances and nonlinearities. The controller is implemented at the machine-side inverter and validated in MATLAB/Simulink under varying wind and load conditions. Comparative results demonstrate that the proposed FFOBC significantly outperforms conventional sliding mode control in terms of overshoot reduction, steady-state accuracy, response smoothness, and total harmonic distortion minimization. Furthermore, the proposed strategy improves energy conversion efficiency, reduces mechanical and electrical stress, and ensures stable power injection into the grid. These findings highlight the potential of the proposed intelligent control framework to support sustainable, resilient, and high-quality wind energy integration in future smart power systems. Full article

A new fractional dynamic sliding mode control (FD-SMC) framework is introduced to reduce chattering in the control of fractional-order chaotic systems. In this method, chattering is eliminated by placing a fractional integrator before the system control input. As a result, the augmented system has a higher dimension than the original system, meaning that additional states are introduced. Effective control therefore requires identifying or estimating these new states or the corresponding plant model. To address this issue, a robust optimal fractional loop-transfer-recovery observer (ROF-LTRO) is developed. Furthermore, the key advantage of sliding mode control (SMC)—its invariance to matched uncertainties—is often lost in many plants such as chaotic systems, because many of them contain mismatched uncertainties. To restore and extend the invariance property, multiple sliding surfaces combined with a virtual control input are employed. In addition, the proposed FD-SMC and ROF-LTRO do not rely on prior knowledge of uncertainty bounds, which is beneficial for practical implementation. Then, a two-stage design procedure based on two-surface definition is presented, and simulation results are provided for the extended fractional Duffing–Holmes chaotic system (EF-DHCS) under both matched and mismatched uncertainties. Full article

This article addresses the trajectory tracking control problem for quadrotor unmanned aerial vehicles (UAVs) subject to complex external disturbances and parameter uncertainties. To balance disturbance rejection with control signal smoothness, a practical predefined-time control scheme incorporating variable exponent coefficients (VEC) is proposed. First, a variable exponent practical predefined-time disturbance observer (VEC-PPTDO) is designed to dynamically estimate and compensate for unknown aerodynamic disturbances. Additionally, a practical predefined-time fractional-order sliding mode control (VEC-PPTFOSMC) scheme is developed, which fuses fractional-order calculus with VEC reaching laws to accelerate convergence and mitigate high-frequency chattering. Based on Lyapunov stability theory, the practical predefined-time stability of the entire closed-loop system is rigorously proven. Finally, comparative simulations under severe stochastic disturbances validate the proposed framework. Quantitative results demonstrate that the proposed scheme achieves a steady-state convergence time of 0.95 s. Compared to the integer-order benchmarks, the proposed method reduces the convergence time by an average of 15.2%, while decreasing the root mean square error (RMSE) and integral absolute error (IAE) by an average of 13.4% and 14.5%, respectively. Consequently, the proposed architecture enhances the dynamic tracking precision, control efficiency, and operational robustness of the quadrotor system. Full article

In this paper, a composite control framework integrating feedback linearization, an extended state observer, and an adaptive fractional-order sliding-mode controller is presented for autonomous underwater vehicles operating under uncertain hydrodynamics and external disturbances. The proposed algorithm, named adaptive fractional-order sliding-mode control with extended state observer, aims to enhance trajectory-tracking accuracy, disturbance rejection, and robustness against model uncertainties beyond what is offered by conventional active disturbance rejection control and integer-order sliding-mode control. First, a fractional-order sliding surface with an extended state observer is introduced to estimate and compensate lumped disturbances, where the fractional operator provides intrinsic filtering and memory effects to reduce chattering. Second, an adaptive exponential reaching law with smooth switching is formulated to overcome the trade-off between convergence speed and chattering, and a Levant differentiator is employed for sensorless velocity estimation. Finally, the uniform ultimate boundedness of the closed-loop system is proved via Lyapunov stability theory. Comparative simulation studies on step, sinusoidal, and circular trajectories under external disturbances, measurement noise, and 50% parametric uncertainties demonstrate that the proposed controller achieves zero overshoot, suppresses position fluctuations by 97%, and reduces root mean square tracking errors by 38–70% relative to conventional methods, confirming its superior performance. Full article

In this paper, a nonsingular fixed-time terminal sliding mode control (NFTSMC) strategy based on a fixed-time adaptive sliding mode disturbance observer (FASMDOB) is proposed for a space robot in the presence of dynamic uncertainties and external disturbance. Firstly, based on fixed-time theory, a novel FASMDOB is designed to mitigate the impacts of the lumped disturbance including dynamic uncertainties and external disturbance, improving the robustness of the control system and utilizing an adaptive technique to reduce chattering. Additionally, compared to finite-time disturbance observers (FTDOB), FASMDOB converges estimation errors to zero within a fixed time, regardless of the information about the initial states of the system. Next, a nonsingular fixed-time terminal sliding mode (NFTSM) surface is developed for the following control system design. By replacing the high-order fractional term with a piecewise function, the singularity problem in conventional terminal sliding mode control is effectively avoided. Combining FASMDOB and NFTSM surface, a FASMDOB-based NFTSMC strategy is developed, which guarantees the fixed-time convergence of the sliding mode surface and tracking errors. Notably, the proposed NFTSMC method utilizes the arctangent function to construct the reaching law, improving the performance of the control system. Lastly, based on Lyapunov theory, the fixed-time stability of the proposed control system is rigorously proven. With several comparative simulations being conducted, the feasibility and effectiveness of the proposed FASMDOB-based NFTSMC strategy are verified and highlighted. Full article

PMSM-based flywheel energy storage systems require fast and robust speed regulation in the presence of parameter uncertainty, load disturbances, and measurement noise, while avoiding the cost and reliability limitations associated with mechanical encoders. This paper proposes a sensorless control framework that combines a fractional-order sliding-mode speed controller with a fractional-order sliding-mode observer. To improve dynamic performance, an improved hybrid Aquila Optimizer–African Vulture Optimization Algorithm (IHAOAVOA) is employed to tune the controller parameters, while the observer follows the proposed robust sensorless design. Simulation results show that at the 1000 rpm operating point under a 20 N·m load disturbance, the proposed method limits the startup overshoot to about 0.24%, compared with 8.02% for the PI control and 9.74% for the conventional sliding-mode control. After the disturbance is introduced at $\mathrm{t}=1.0$ s, the speed drop of the proposed method is limited to 2.80%, whereas those of the PI control and conventional sliding-mode control reach 7.20% and 5.60%, respectively. At the 8000 rpm operating point under an 80 N·m load disturbance, the proposed method maintains the same advantage, with an overshoot of about 0.04% and a speed drop of 1.88%, both lower than those of the two benchmark controllers. In sensorless operation, the sensorless scheme with the IHAOAVOA-tuned speed controller also improves transient estimation performance. At the 1000 rpm operating point, the maximum startup speed estimation error is reduced from 41.8 r/min to 34.8 r/min. At the 8000 rpm operating point, the estimation error enters the ±10 r/min band at 0.0671 s, compared with 0.0718 s for the PSO-tuned case. The electromagnetic torque responses further indicate that the proposed tuning strategy improves transient torque smoothness while maintaining comparable steady-state torque behavior. These results demonstrate that the proposed control framework provides an effective balance among fast dynamic response, disturbance rejection, sensorless estimation accuracy, and electromechanical transient smoothness for PMSM-based flywheel energy storage applications. Full article

This paper proposes an adaptive wavelet neural network nonsingular fast terminal sliding mode control strategy based on a finite-time framework for a space robot system under external disturbances and model uncertainties. Firstly, the dynamic model of space robot is established based on the second Lagrange equation. Unlike sliding mode control, which converges asymptotically, terminal sliding mode control (TSMC) has been proposed to ensure finite-time convergence for a space robot system. Based on the aforementioned TSMC framework, the fast terminal sliding mode control (FTSMC) is proposed to enhance system convergence rate. However, TSMC exhibits a singularity issue attributed to the presence of negative fractional order. To avoid this issue, a nonsingular fast terminal sliding mode controller (NFTSMC) has been proposed. The controller is designed to integrate linear and nonlinear terms into a novel nonsingular fast terminal sliding mode surface. The method achieves fast finite-time convergence concurrently with improved robustness, while effectively avoiding singularities. To compensate for external disturbances and model uncertainties in the space robot system, this paper proposes the combination of wavelet neural network (WNN) for the real-time estimation of lumped uncertainties. Network parameters are dynamically adjusted via an adaptive law to mitigate chattering effectively and enhance trajectory tracking precision. Utilizing Lyapunov stability theory and numerical simulations, the space robot system’s stability is rigorously proven and the controller effectiveness is validated. Compared with the traditional NFTSMC, the proposed control strategy reduces the convergence time by 20.74%. In the case of trajectory tracking comparison, the root mean square error (RMSE) improves by 35.85%, the mean tracking error improves by 63.29%, the integral of absolute error (IAE) improves by 29.37%, and the integral of time-weighted absolute error (ITAE) improves by 93.06%. Additionally, a comparative simulation with RBFNN is included in this paper. Compared with RBFNN, the proposed control strategy reduces input torque energy consumption by 77.36% and improves control smoothness by 87.03%, quantitatively demonstrating the effectiveness of the proposed control strategy. Full article