Search Results (591)

An active damping control technique based on improved linear active disturbance rejection control (LADRC) is suggested to address the inadequate damping of doubly fed induction generator (DFIG) systems coupled to the grid using series compensation capacitors. Conventional LADRC still has certain limitations under complicated operating conditions, primarily because of its inadequate periodic disturbance estimate capabilities, which limit the system’s dynamic performance and disturbance-rejection capability. An enhanced LADRC scheme is created for the inner current loop of the rotor-side converter (RSC) in the DFIG system in order to lessen these restrictions. To enable a real-time estimate and adjustment of sub-synchronous disturbances, a decoupled linear extended state observer (LESO) is first proposed. In order to effectively attenuate both sub-synchronous oscillation and periodic disturbances, a composite control structure with enhanced suppression capability is constructed by incorporating an improved repetitive control scheme into the linear state error feedback law. The results show that the improved LADRC significantly enhances damping performance and disturbance rejection capability in the subsynchronous frequency range, suppressing active power oscillations within approximately 0.3 s based on a ±10% settling band. Compared with the conventional LADRC, the average THD of the grid current is reduced from 3.43% to 0.56%. Full article

To improve the machining ability of serial robots, an optimized SSI method is proposed to realize online modal identification. Firstly, the method employs the NExT technology, modal confidence factor, and modal assurance criterion to improve the parameters’ identification accuracy. Next, the machining vibration data at key points in the path of the machining robot are used to identify the modal frequency and damping ratio. Finally, the experimental results show that the optimized SSI method can achieve estimation errors within 7%, and the method of optimized SSI is more accurate than the traditional SSI method. Therefore, if only the modal frequency and the damping ratio are concerned, the method can realize the online recognition of modal parameters in the cutting path of the machining robot, which can provide key input parameters for the process planning and optimization. Full article

Fishing buoys are confronted with the problems of insufficient power supply and loss. To address these challenges, a small innovative fishing buoy equipped with an internal pendulum and powered by wave energy is designed. Its structural shape enables it to maintain a stable surfing state, thereby facilitating more efficient wave energy capture. Free decay tests and wave energy capture tests were conducted via numerical and experimental simulations. A mathematical model was proposed and validated using experimental data. Through free decay tests, the natural periods of the device in heave and pitch motions were obtained, which ranged from 1.0 to 1.42 s. The results of the wave energy capture tests indicate that the device can capture approximately 300 mW of electrical power under small-wave conditions. Additionally, the mechanical damping coefficient of the buoy-pendulum system was estimated to be 0.15 Nms/rad, and the mechanical efficiency of the wave energy converter was 15%. Preliminary optimization was carried out through numerical model simulation, which is conducive to the refined design of the device. This study provides a reference for the development and design of similar wave energy conversion devices. Full article

Tailings are unconventional geomaterials that require dynamic characterisation due to seismic hazards at several storage facilities. Due to the anthropic origin of these materials, their dynamic properties differ from those reported for natural soils. In particular, the damping ratio is a relevant parameter that controls the dynamic response of tailings storage facilities. It can be estimated using different experimental methods. The objective of this research is to disclose the results obtained through laboratory tests in which the damping ratio was evaluated independently by Half-Power Bandwidth or the free-vibration decay methods. A comprehensive testing plan comprising resonant column tests and free-vibration decay tests was carried out on three types of tailings from the Riotinto mines (Huelva, Spain): Cerro Salomón Sand (CSS), High-Density Sludge (HDS), and Copper Lamas (CL). These tests were carried out under different effective consolidation pressures and torsional excitations. The results allowed the establishment of a series of relationships between the testing conditions and the identification of differences between the methods for tailings. Full article

In tunnel engineering, the integration of aseismic materials and structural designs has become a prevalent strategy to reduce earthquake-induced damage. However, previous studies on the seismic performance of tunnel structures predominantly employed deterministic methods, overlooking the spatial variability of the surrounding rock mass. This oversight often leads to an overestimation of structural performance, posing potential risks to the project. This study develops a probabilistic framework based on random field theory to evaluate the aseismic performance of tunnel linings incorporating a rubber–sand–concrete (RSC) constrained damping layer. The analysis systematically evaluates the aseismic performance of RSC across varying peak ground acceleration (PGA) levels and tunnel depth conditions. The findings are compared with results from traditional deterministic approaches. The probabilistic analysis indicates the following: (1) a reduction of approximately 70% in the dispersion of maximum principal stresses across various PGAs; (2) a decrease in RSC’s aseismic performance with greater burial depths, though it remains substantial overall, and (3) a reduction in the failure probability from 31.8% to 16.3% at PGA = 1.2 g. Furthermore, deterministic methods tend to produce overly optimistic estimates of tunnel aseismic performance, highlighting the need for probabilistic analysis. Full article

In this paper, we investigate the partial approximate controllability of a class of fractional diffusion control systems with three-parameter damping and nonlinear perturbations. First, based on the theory of $(\mu ,\nu ,\xi ,e,k)$-resolvent families developed in our previous work, we define the mild solution of the system. Then, by constructing a proper objective functional and using the strict convexity, we prove the existence and uniqueness of the minimal norm control. Furthermore, employing the Arzelà–Ascoli theorem and variational inequalities, we establish the precompactness of the solution family and derive the key controllability estimate. Finally, we provide an example to illustrate the effectiveness of our theoretical results. Full article

In the context of Industry 5.0, human–robot collaboration increasingly demands intuitive, safe, and sensorless interaction for tasks such as hand-guided teaching and concurrent manipulation. However, conventional admittance control systems are prone to instability due to abrupt changes in human arm stiffness and their reliance on accurate dynamic models. To address these challenges, this paper proposes a sensorless external force estimation and variable admittance control method that models robot dynamic uncertainties and interaction forces as normally distributed stochastic quantities. An improved particle swarm optimization algorithm is introduced to calibrate the variance parameters, enhancing estimation accuracy and robustness. Furthermore, an energy-based variable admittance control strategy is developed, which preserves system passivity by adaptively adjusting inertia and damping gains based on real-time energy variations. The proposed method was validated on a redundant robot platform. Experimental results show that the external force and torque estimation errors remain below 3 N and 3 N.m, respectively, with lower detection delays and errors than those of a first-order generalized momentum observer in collision detection. Variable admittance experiments demonstrate that the system maintains passivity and stable interaction even under sudden arm stiffness changes. The approach is well-suited for industrial applications requiring safe, sensorless, and compliant human–robot collaboration. Full article

Force rebalance-type accelerometers are mainly used in inertial navigation systems of aircraft, and the characterization of the resulting squeeze film damping (SFD) is essential for estimating dynamic response characteristics of these accelerometers. In this study, a methodology for modeling SFD and experimentally verifying this model for force rebalance-type accelerometers is presented. Modeling of the SFD effect involves determining an effective damping coefficient as a function of pendulum displacement. Damping force and pressure distribution due to SFD are obtained for a range of pendulum displacements via finite element analysis (FEA). The accelerometer is modeled as both an open- and closed-loop system, where an identified damping model for SFD is also used. The open-loop model is verified by comparing the step response of the system, and the closed-loop model is verified by comparing the frequency and shock responses of the system via simulations and experiments. Simulation and test results of both open- and closed-loop systems show close agreement. The presented results indicate that in systems with similar dimensions and material properties, damping due to SFD in a force rebalance accelerometer can be accurately modeled as a function of pendulum displacement using the method described in this research study. Full article

To address the actuator fault problem faced by underactuated surface vessels (USVs), this study develops an active fault-tolerant control scheme based on finite-time output feedback. First, a finite-time neural terminal homogeneous state observer with a portional-integral structure is established. High-precision pose reconstruction enables finite-time synchronous reconstruction of unmeasured states. This allows unknown nonlinearities to be explicitly expressed online and incorporated into the compensation channel, significantly reducing the sensitivity of modeling errors to control performance. A neural damping mechanism is used to structurally reconstruct uncertain dynamics and loss-of-effectiveness (LOE) fault factors within the system, thereby constructing an online approximator to achieve real-time identification and compensation of composite uncertainties. This integrates the unknown nonlinearities and fault effects of the original system into an online-updatable estimation channel. Adopting a backstepping-based design methodology, a finite-time hybrid event-triggered control (ETC) architecture is further constructed. By introducing an event-triggered update mechanism at the control layer, the real-time continuous control signal is transformed into a discrete update. Based on Lyapunov stability theory, a comprehensive analysis is carried out to verify the stability of the proposed control scheme. Numerical simulations are finally carried out to validate the effectiveness of the scheme. Simulation results show that the tracking error is reduced by about $93\%$ and $60\%$ compared to the comparison scheme. Full article

Seismic-induced torsional response remains a significant barrier to achieving resilient and sustainable building foundations, as traditional passive isolation systems often fail to regulate rotational motion effectively. This study examines an adaptive gyroscopic feedback-based foundation control system designed to provide automated torsional seismic mitigation. The proposed system integrates real-time angular velocity sensing using MEMS gyroscopes, Kalman filter state estimation, and an adaptive Linear Quadratic Regulator to modulate damping in response to changing ground motion. A single-degree-of-freedom torsional foundation model was developed and evaluated in GNU Octave 8.4.0/MATLAB R2024a Simulink using the recorded El Centro 1940 NS earthquake input. The adaptive controller achieved notable improvements, reducing total vibration energy by 69%, peak angular displacement by 47.6%, and RMS angular velocity by 39.5% relative to the uncontrolled case, while keeping control energy below 19% of the seismic input. These results demonstrate that gyroscopic feedback enhances damping, limits torsional resonance, and stabilises foundation behaviour under actual earthquake excitation. The system’s low energy requirement, compatibility with embedded hardware, and automated response characteristics underscore its potential for integration into sustainable and intelligent foundation designs. While results are demonstrated using the El Centro 1940 record as a benchmark, broader generalisation will be established through multi-record suites and uncertainty quantification in future work. The study highlights a feasible pathway for advancing automated seismic protection in buildings through active, sensor-driven torsional control. Full article

The large-scale grid integration of photovoltaic systems, accompanied by extensive power electronic equipment, exacerbates the risk of sub-synchronous oscillation (SSO) and poses a serious threat to the safe and stable operation of modern power systems. To address the limitation that traditional additional damping controllers rely on accurate mathematical models of the system, this paper applies model-free adaptive control (MFAC) to suppress sub-synchronous oscillation in photovoltaic systems. The proposed method requires no prior identification of the plant model and achieves adaptive control by online estimation of pseudo-partial derivatives using only system input-output data, with parameters optimized by particle swarm optimization. Simulation results show that the proposed controller can effectively shorten the settling time and suppress oscillations However, for oscillations induced by different mechanisms, it still has the limitation of requiring parameter re-optimization. This approach provides a new model-free technical pathway for sub-synchronous oscillation mitigation in grid-connected photovoltaic systems. Full article

The increasing penetration of rooftop photovoltaic (RTPV) systems in low-voltage (LV) distribution networks introduces challenges such as voltage rises, reverse power flow, and reduced hosting capacity, thereby necessitating effective active power regulation (APR) in module-level micro-inverters. This paper proposes a dual-layer control framework for a 250 watt-peak (Wp) three-switch rooftop PV micro-inverter, integrating quantum-behaved particle swarm optimization with reinforcement learning (QPSO-RL) for accurate maximum power point tracking (MPPT) and a linear quadratic regulator (LQR) for reserve-aware APR. The QPSO-RL algorithm improves available-power estimation under varying irradiance, temperature, and partial-shading conditions, while the LQR-based controller ensures fast, well-damped, and grid-compliant power regulation. The proposed framework was developed and validated using MATLAB/Simulink 2024 for simulation studies and LabVIEW with NI myRIO 2022 for real-time hardware implementation. Both simulation and experimental results confirm that the proposed method achieves 99.5% MPPT accuracy, convergence within 20 ms, grid-injected current total harmonic distortion (THD) below 3%, and a near-unity power factor. In addition, the reserve-based regulation strategy improves feeder compliance and reduces converter stress, thereby supporting reliable rooftop PV integration. These results demonstrate that the proposed QPSO-RL + LQR framework offers a practical and intelligent solution for high-performance, grid-supportive rooftop PV micro-inverter applications. Full article

Structure-preserving trajectory tracking control for a six-degree-of-freedom robotic manipulator is developed within the port-Hamiltonian framework. Error Hamiltonian is constructed by incorporating configuration and momentum tracking errors into the system energy. Based on this formulation, a momentum-based tracking controller with feedforward compensation and damping injection is derived without coordinate transformations or matching conditions. A disturbance estimator is further introduced to compensate unknown external torques. Energy-based analysis proves nominal closed-loop stability and uniform ultimate boundedness in the presence of estimation errors. Simulation results on a full rigid-body manipulator demonstrate accurate trajectory tracking under coupled and high-speed joint motions. Full article

In this work, we study a one-dimensional coupled hyperbolic–parabolic system modeling the dynamics of swelling soils under thermodiffusion effects. The model describes the interaction between the deformation of the solid skeleton, the pore fluid motion, the temperature variation, and a diffusive process formulated through chemical potential. Under mixed boundary conditions and without introducing additional mechanical damping or imposing restrictive relations among the physical parameters, we prove exponential stability of the system. Our analysis is based on the energy method. In contrast to the standard energy functional commonly used in related thermodiffusion models, we introduce a modified positive energy functional better adapted to the coupled structure of the system. By combining this energy with suitable auxiliary functionals, we construct an appropriate Lyapunov functional and derive an exponential stability estimate. Our result shows that thermodiffusion alone yields sufficient dissipation for exponential stabilization, complementing earlier works where exponential stability requires extra damping mechanisms or equal wave-speed assumptions. Full article

Continuous impact vibrations caused by uneven road surfaces (such as speed bumps) can significantly reduce the trajectory tracking accuracy of mobile manipulator. This study proposes for the first time an integrated framework combining a semi-active magnetorheological elastomer (MRE) intelligent isolation system with an active trajectory tracking controller to improve the operational accuracy of mobile manipulator under continuous impact excitation, and numerically evaluates the effect of the MRE isolation system. The working principle and design method of the MRE isolation system for mobile manipulators are described, and a multi-layer MRE isolator is fabricated and experimentally characterized. A semi-active control strategy is developed to adaptively adjust the stiffness and damping of the isolator based on continuous impact input. To further compensate for residual disturbances transmitted through the isolator, an enhanced computational torque control (CTC) and proportional-derivative (PD) controller with predefined-time disturbance observer (DOB) is designed for the mobile manipulator. This ensures that the disturbance estimate converges within a predefined time window, thereby improving the robustness of the closed-loop system. By constructing a comprehensive multibody dynamics model coupling the vehicle, the MRE isolator, and the manipulator, vibration transmission is analyzed and trajectory tracking performance is evaluated. Simulation results under continuous road impact excitation demonstrate that the proposed semi-active MRE intelligent isolation system can significantly suppress base vibration and greatly improve the trajectory tracking accuracy of the mobile manipulator end-effector and its joints. This study proves the feasibility of the semi-active MRE isolation system in the trajectory tracking application of mobile manipulator and provides a new approach for the collaborative design of intelligent vibration isolation and control strategies for mobile robot systems operating in harsh and frequently impacted environments. Full article