Search Results (9,015)

To improve solar energy utilization efficiency, address control precision issues in solar panel tracking systems, and strengthen the sustainable supply capacity of clean renewable energy, this study proposes an innovative variable universe fuzzy adaptive PID control algorithm for high-precision solar tracking systems. Based on this algorithm, a fusion scheme combining a high-precision four-quadrant detector and GPS positioning is employed to achieve real-time and precise positioning of the tracking system. The azimuth and elevation angle deviations between the real-time solar rays and the system’s actual position are calculated and used as input signals for the tracking control system. These deviations are dynamically corrected by the variable universe fuzzy adaptive PID controller, which drives a stepper motor to achieve high-precision solar tracking. The results demonstrate that, under ideal operating conditions, the proposed algorithm reduces the steady-state error by 3.5–4.9°, shortens the settling time by 4.4–5.8 s, decreases the rise time by 0.6 s, lowers the overshoot by 18–19%, and reduces the disturbance recovery time by 1.3 s. These improvements significantly enhance tracking accuracy and dynamic response efficiency. Under complex operating conditions, the algorithm reduces the steady-state error by 3.2–5.9°, shortens the settling time by 5.4–6.2 s, decreases the rise time by 0.7 s, lowers the overshoot by 17.5–19%, and reduces the disturbance recovery time by 1.5 s, thereby ensuring stable and efficient solar tracking and maintaining continuous energy capture. By quantitatively optimizing multiple performance metrics, this algorithm significantly enhances the control precision of solar panel tracking and improves solar energy utilization efficiency. It holds substantial significance for promoting the transition of the energy structure toward cleaner and more sustainable sources. Full article

The vertical actuation of multi-axis seismic simulators usually requires a redundant parallel scheme for high load capacity. Due to geometric over-constraints, the internal force coupling and the nonlinear hysteresis are high; thus, waveform reproduction quality and structural fatigue may result. A displacement–force dual closed loop cooperative control mechanism can address these problems. First, a real-time kinematic model is developed to overcome the platform pose via actuator extension, and second, a dynamic force balance loop is introduced to actively redistribute the load components. In addition, a fuzzy PID controller is incorporated to optimize gain scheduling online, compensating for hydraulic nonlinearities and time-varying structural parameters. In the experiment on a 3 × 3 m 6-DOF shaking table, the presented method performs very favorably compared to traditional methods. Under broadband random excitation, the THD of acceleration waveform drops from 15.2% (single-loop control) to 3.2%, and the internal momentum oscillation amplitude is suppressed by over 70%. The results show that our proposed method eliminates internal force dependence while maintaining high precision trajectory tracking for seismic simulation. Full article

Wireless Body Area Network (WBAN) is an emerging medical health monitoring technology. However, WBANs encounter critical challenges in balancing reliability, energy efficiency, and Quality of Service (QoS) requirements for life-critical medical data. The design of its Medium Access Control (MAC) protocol has challenges since dynamic body-shadowing effects and heterogeneous traffic patterns. In this paper, we propose the Nash Bargaining Rate-optimization MAC (NBR-MAC), a hybrid MAC protocol that integrates TDMA-based Guaranteed Time Slots (GTS) with CSMA/CA-based contention access. Unlike traditional schemes, we model the rate allocation as an Asymmetric Nash Bargaining Game, introducing a rigorous disagreement point to guarantee minimum service for critical nodes. The utility function is normalized to resolve dimensional inconsistencies, incorporating sensor priority, buffer status, and channel quality. The Nash Bargaining solution is derived after proving convexity and verifying the axioms. Superframe time slots are allocated based on sensor data priority. Simulation results demonstrate that the proposed protocol enhances transmission success ratio and throughput while reducing packet age and energy consumption under different load conditions. Full article

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into Internet of Things (IoT) ecosystems for applications such as surveillance, disaster response, environmental monitoring, and logistics. These missions demand reliable and secure communication between UAVs and cloud platforms for command, control, and data storage. However, UAV communication channels are highly vulnerable to eavesdropping, spoofing, and man-in-the-middle attacks due to their wireless and often long-range nature. Traditional cryptographic schemes either impose excessive computational overhead on resource-constrained UAVs or lack sufficient robustness for cloud-level security. To address this challenge, we propose a dual-layer encryption architecture that balances lightweight efficiency with strong cryptographic guarantees. Unlike prior dual-layer approaches, the proposed framework introduces a context-aware adaptive lightweight layer for UAV-to-gateway communication and a hybrid post-quantum layer for gateway-to-cloud security, enabling dynamic cipher selection, energy-aware key scheduling, and quantum-resilient key establishment. In the first layer, UAV-to-gateway communication employs a lightweight symmetric encryption scheme optimized for low latency and minimal energy consumption. In the second layer, gateway-to-cloud communication uses post-quantum asymmetric encryption to ensure resilience against emerging quantum threats. The architecture is further reinforced with optional multi-path hardening and blockchain-assisted key lifecycle management to enhance scalability and tamper-proof auditability. Experimental evaluation using a UAV testbed and cloud integration shows that the proposed framework achieves 99.85% confidentiality preservation, reduces computational overhead on UAVs by 42%, and improves end-to-end latency by 35% compared to conventional single-layer encryption schemes. These results confirm that the proposed adaptive and hybridized dual-layer design provides a scalable, secure, and resource-aware solution for UAV-to-cloud communication, offering both present-day practicality and future-proof cryptographic resilience. Full article

This paper proposes a zero-voltage-switching (ZVS) synchronous buck converter employing a digital hybrid control scheme with variable slope compensation. By using an auxiliary-switch network and a digital controller to sense voltage and current, the system can automatically adjust the slope-compensation parameters according to the input and output conditions, thereby enhancing stability over a wide operating range. The proposed method effectively suppresses the reverse-recovery current spike of the synchronous rectifier during continuous conduction mode (CCM) operation and enables the main switch to achieve ZVS, reducing switching loss and improving efficiency. A laboratory prototype with an input voltage range of 30–160 V and output voltage levels of 24 V, 48 V, and 96 V at 5 A is developed to verify the feasibility of the proposed architecture. Full article

This paper presents a control architecture based on Pixhawk4 to address the transition mode control issue of a tilt-rotor tricopter. While the classical PID controller designed for the rotor mode can handle most engineering applications under normal environmental conditions, it does not fully consider disturbances such as those arising from internal perturbations or the external environment. In response, this paper proposes a controller design with disturbance observation to meet the robustness requirements of the unmanned aerial vehicle (UAV) under perturbed conditions. For the state-constrained control problem of the UAV, the original model is simplified, and a three-channel model for control purposes is introduced. By incorporating a barrier Lyapunov function, the state constraint problem of the UAV is solved, ensuring a smooth transition from rotor mode to fixed-wing mode. To address the high complexity of virtual control law derivatives in backstepping control, a filter is used to estimate the derivatives of the UAV′s virtual states, and a linear extended state observer is introduced to estimate external and transitional disturbances during flight. Lyapunov theory is employed to ensure the closed-loop stability of the control scheme. Finally, inspired by the hunting process of aquilas, the Aquila Optimizer (AO) optimization algorithm is applied to optimize the controller’s hyperparameters, further enhancing the reliability and transient performance of the control system. Full article

Understanding the behavior of light non-aqueous phase liquids (LNAPLs) in urban subsurface environments is essential to developing effective pollution control strategies, designing remediation systems, and managing waste and resources sustainably. Oil leakage from urban industrial facilities, underground pipelines, and fueling systems often leads to contamination that is challenging to characterize due to complex soil structures, limited access beneath densely built infrastructure, and dynamic groundwater conditions. In this study, we integrate a large-scale soil tank experiment with multiphase flow simulations to elucidate LNAPL distribution mechanisms under fluctuating groundwater conditions. A 2.4-m-by-2.4-m-by-0.6-m soil tank was used to visualize oil movement with high-resolution multispectral imaging, enabling a quantitative evaluation of saturation distribution over time. The results showed that a rapid rise in groundwater can trap 60–70% of the high-saturation LNAPL below the water table. In contrast, a subsequent slow rise leaves 10–20% residual saturation within pore spaces. These results suggest that vertical redistribution caused by groundwater oscillation significantly increases residual contamination, which cannot be evaluated using static groundwater assumptions. Comparisons with a commonly used NAPL simulator revealed that conventional models overestimate lateral spreading and underestimate trapped residual oil, thus highlighting the need for improved constitutive models and numerical schemes that can capture sharp saturation fronts. These results emphasize that an accurate assessment of LNAPL contamination in urban settings requires an explicit consideration of groundwater fluctuation and dynamic multiphase interactions. Insights from this study support rational monitoring network design, reduce uncertainty in remediation planning, and contribute to sustainable urban environmental management by improving risk evaluation and preventing the long-term spread of pollution. Full article

Steering angle control in self-driving cars is usually organized in layers combining trajectory planning, path tracking, and low-level actuator control. The steering controller converts the planned path into a desired steering angle and then ensures accurate tracking by the electric power steering (EPS). However, automotive electric power steering (AEPS) systems face many problems caused by model uncertainties, disturbances, and unknown system dynamics. In this paper, a robust finite-time control strategy based on an adaptive backstepping scheme is proposed to handle these problems. First, radial basis function neural networks (NNs) are designed to approximate the unknown system dynamics. Then, an adaptive sliding-mode disturbance observer (ASMDO) is introduced to address the impacts of the lumped disturbance. Enhanced control performance for the AEPS system is implemented using a combination of the above technologies. Numerical simulations and a hardware-in-the-loop (HIL) experimental verification are performed to demonstrate the significant improvement in performance achieved using the proposed strategy. Full article

Low-level jets (LLJs) are common strong wind structures in the atmospheric boundary layer. They have important impacts on aviation safety, wind energy utilization and pollutant dispersion. However, the formation mechanisms of LLJs are complex. Traditional parameterization schemes and numerical models still show limitations in forecasting LLJ occurrence and resolving their structures. In this study, wind lidar, near-surface turbulence and gradient meteorological observations from the Semi-Arid Climate and Environment Observatory of Lanzhou University are combined to construct a multi-source low-level dataset. Four processing modules are designed, including multi-source data fusion, turbulence preprocessing, turbulence intermittency metrics and LLJ identification, to overcome the constraints of single-platform observations. Six commonly used machine learning algorithms (LightGBM, XGBoost, CatBoost, K-nearest neighbors, Balanced Random Forest, and ExtraTrees) are compared. A two-stage classification–regression framework is then adopted. LightGBM is used for LLJ occurrence, and CatBoost is used for LLJ height and intensity, to build an LLJ-2Stage prediction system. The system performs automatic LLJ identification and predicts jet intensity and core height. For LLJ occurrence, the harmonic-mean F1-score of precision and recall reaches 0.820. The coefficient of determination R² is 0.643 for height prediction and 0.794 for intensity prediction. Both the classification and regression parts show good accuracy and stability. The SHAP method is further applied to assess model interpretability and to identify key predictors that control LLJ occurrence, height and intensity. Results indicate that thermal variables, such as net radiation (Rn) and sensible heat flux (H), dominate LLJ occurrence and structural changes. The strength of turbulence intermittency provides valuable supplementary information for locating the LLJ core height. Two representative nocturnal LLJ cases further show a consistent near-surface evolution during the LLJ period, with enhanced TKE and reduced H, followed by a gradual recovery after decay, while Rn remains persistently low, consistent with the SHAP-indicated effects. The proposed framework predicts LLJ occurrence and structural evolution and is of significance for improving understanding of boundary layer processes, air-pollution control, wind energy utilization and low-level aviation safety. Full article

With rapid advances in nanotechnology and synthetic biology, biological nanonetworks are emerging for biomedical and environmental applications within the Internet of Bio-NanoThings. While they rely on molecular communication, experimental validation remains limited, especially for non-ideal effects such as molecular accumulation. In this work, we present a novel table-top experimental system that emulates the core functionalities of a biological nanonetwork and is straightforward to reproduce in standard laboratory environments, also making it suitable for educational demonstrations. To the best of our knowledge, this is the first experimental platform that incorporates two end nodes capable of acting interchangeably as transmitter and receiver, thereby enabling true bidirectional molecular communication. Information transfer is realized through controlled release, advection and diffusion of molecules, using molecular concentration coding analogous to concentration shift keying, while the receiver decodes messages by comparing measured concentrations against predefined thresholds. Based on the measurements reported herein, the drop-based algorithm substantially outperforms the threshold-based scheme. Specifically, it reduces first-message latency by more than 2.5× across the tested volumes and reduces latest-message latency by up to 71%, providing approximately 3.7× better message delivery. A key experimental outcome is the observation of channel saturation: beyond a certain operating period, residual molecules accumulate and effectively saturate the medium, inhibiting reliable further message exchange until sufficient clearance occurs. This saturation-induced “channel memory” emerges as a fundamental practical constraint on sustained communication and achievable data rates. Overall, the proposed platform provides a scalable, controllable, and experimentally accessible testbed for systematically studying signal degradation, saturation, clearance dynamics, and throughput limits, thereby bridging the gap between theoretical models and practical implementations in the Internet of Bio-NanoThings era. Full article

Although interest in tidal energy has increased in recent years, its development remains significantly behind that of other renewable sources such as solar and wind energy. This delay is primarily caused by the complex and harsh ocean environment, which imposes significant constraints on operational systems. This paper proposes a new approach to the design and control of a marine current turbine (MCT) emulator without a pitch mechanism, operating in real time below the rated marine current speed.The emulator control strategy integrates two approaches: predictive control for regulating the speed of the DC machine, and a Linear Quadratic Regulator (LQR) control scheme for maximizing power extraction from the marine current. Our experimental results demonstrate the effectiveness of the proposed hybrid control strategy, which allows precise tracking of reference signals and stable regulation of the direct current machine (DCM) speed, thereby ensuring synchronization with the turbine’s rotational speed. This approach ensures optimal and robust performance over the entire range of marine current variations. Full article

Maintaining stable pressure in the oxidation–compressor section of purified terephthalic acid (PTA) plants is essential for ensuring efficient and reliable operation. Conventional single-loop proportional integral derivative (PID) controllers frequently perform inadequately because of the large pressure drop between the compressor discharge and reactor inlet, which should ideally remain at approximately 1.2 kg/cm² above the reactor pressure setpoint but can reach up to 2.8 kg/cm² due to downstream vapor-phase disturbances. Through this study, we aimed to address this issue by developing a robust cascade pressure control strategy to improve pressure stability and reduce energy losses. Dynamic process models were constructed using system identification techniques to represent real plant behavior, and the best-performing models—identified based on minimum root mean square error (RMSE)—were determined using the Wade method for pressure indicating controller PIC-101, the Lilja method for PIC-102, and the Smith method for pressure differential indicating controller PDIC-101. The proposed cascade configuration was tuned using the Lopez ISE method and evaluated under representative disturbance scenarios. The results showed that the cascade controller significantly improved pressure control, enhanced disturbance rejection, and lowered the risk of reactor shutdowns compared with the conventional proportional-integral PI-based approach. Overall, this study demonstrated that model-driven cascade control can enhance robustness, operational reliability, and energy efficiency in large-scale PTA oxidation processes. Full article

The efficient design of biohybrid materials requires controlling the interaction between the cell and the material for a wide range of possible combinations. Single cell force spectroscopy (SCFS), an atomic force microscopy (AFM) experimental procedure based on the binding of an individual cell to an AFM cantilever and the assessment of the adhesion force between the cell and a target substrate, represents one of the most promising alternatives to characterize the interaction between cell and material. However, SCFS relies on the efficient binding of the cell to the AFM in order to avoid drawbacks, such as the detachment of the cell. In this work, three different versatile and robust procedures are presented that allow for the binding of either non-adherent (CD4⁺ T-lymphocytes) or adherent (mesenchymal stem cells, MSC) cells to the AFM probe. The three crosslinking strategies comprise (1) the streptavidin/biotin system, (2) sulfhydryl group-based crosslinkers, and (3) “click” (bioorthogonal) chemistry. Additionally, three decoration schemes of the functionalized AFM probes are explored: a specific antibody, concanavalin A, and direct binding of the cell through azide-derivatized membrane proteins. Differences are observed between these alternatives and it is found that the strength of the interaction (in decreasing order) is as follows: specific antibody, concanavalin A, and binding through azide-derivatized proteins. Full article

To address the increasing demands for faster response and higher control accuracy in the braking systems of electric and intelligent vehicles, a novel brake-by-wire actuation unit and its braking force control methods are proposed. The braking unit employs a permanent-magnet linear motor as the driving actuator and utilizes the lever-based force-amplification mechanism to directly generate the caliper force. Compared with the “rotary motor and motion conversion mechanism” configuration in other electromechanical braking systems, the proposed scheme significantly simplifies the force-transmission path, reduces friction and structural complexity, thereby enhancing the overall dynamic response and control accuracy. Due to the strong nonlinearity, time-varying parameters, and significant thermal effects of the linear motor, the braking force is prone to drift. As a result, achieving accurate force control becomes challenging. This paper proposes a model-free adaptive control method based on compact-form dynamic linearization. This method does not require an accurate mathematical model. It achieves dynamic linearization and direct control of complex nonlinear systems by online estimation of pseudo partial derivatives. Finally, the proposed control method is validated through comparative simulations and experiments against the fuzzy PID controller. The results show that the model-free adaptive control method exhibits significantly faster braking force response, smaller steady-state error, and stronger robustness against external disturbances. It enables faster dynamic response and higher braking force tracking accuracy. The study demonstrates that the proposed brake-by-wire scheme and its control method provide a potentially new approach for next-generation high-performance brake-by-wire systems. Full article

This paper presents the development and experimental evaluation of the Athena parallel robot, a novel system designed for robot-assisted pancreatic surgery. The development of the experimental model based on the kinematic scheme, including the command and control system (hardware and software), the calibration procedure, and the performance measurements of the experimental model based on finite element analyses of the 3D model, are also detailed in this paper. Based on these finite element analyses, a region of the robot that introduces clearance during the operation of the experimental model is found. The paper also presents the methodology used for mapping the robot’s workspace with an optical system, which enabled improvements to ensure coverage of the entire pancreas area. The results obtained before and after the mechanical improvements are presented, demonstrating a reduction in clearance by up to 4.1 times following part replacement, as well as a workspace extension that enables the active instrument to reach the entire pancreatic region. Full article