Control Method Research Articles

Compliant assembly of complex aviation plugs combining multi-agent search and variable parameters

Purpose In response to the complex external structure of high-precision aviation plugs, which makes it difficult to search outside the hole and adjust inside the hole during automated assembly. This paper aims to propose an assembly framework that combines multi-agent search and variable parameter compliant control to solve this problem. Design/methodology/approach First, a multi-agent search strategy (MAS) based on Gaussian Mixture Model and Deep Q-Network was proposed to optimize displacement direction and actions, thereby improving search speed and success rate. Then, a variable parameter admittance control method (RL-VPA) based on dual delay depth deterministic policy gradient (TD3) was proposed, which dynamically optimized the internal parameters of the admittance controller and adopted state space discretization to improve convergence speed and assembly efficiency. Findings Compared to spiral search and single-agent search, the average search success rate has improved by approximately 10% and 6.6%. Compared to fixed admittance control and other RL-based methods, the average assembly success rate has increased by approximately 38.6%, 22% and 8.6%. Compared with the training results of the model without state discretization, it was found that state discretization helps the model converge quickly. To verify the generalization ability of the assembly framework, experiments were conducted on three different pin counts of aviation plugs, the assembly success rate reached 86.7%, all of which showed good assembly results. Finally, combining state space discretization to reduce the impact of environmental noise, improve training effectiveness and convergence speed. Originality/value MAS has been proposed to optimize displacement direction and action, improving search speed and success rate. RL-VPA is designed to dynamically optimize the internal parameters of the admittance controller, enhancing the robustness and generalization ability of the model. Additionally, state space discretization is combined to improve training effectiveness and convergence speed.

Satisfaction-Based Optimal Lane Change Modelling of Mixed Traffic Flow and Intersection Vehicle Guidance Control Method in an Intelligent and Connected Environment

Satisfaction-Based Optimal Lane Change Modelling of Mixed Traffic Flow and Intersection Vehicle Guidance Control Method in an Intelligent and Connected Environment

Reinforcement learning-based near-optimal control for discrete time-delay singularly perturbed systems with unmeasurable states

This brief proposes a novel reinforcement learning-based composite near-optimal output feedback (OPFB) control method for discrete time-delay singularly perturbed systems (SPSs) with unknown dynamics and unmeasured system states. Firstly, an optimal control problem of the full-order time-delay SPS is formulated. The singular perturbation techniques are used to obtain the reduced-order subsystems and equivalent subproblems. Then, a state reconstruction method is presented to represent the state in terms of available input and output data. In addition, a reinforcement learning (RL) algorithm based on input and output data is developed. Theoretical analyses are discussed on the convergence of the proposed algorithm and the asymptotical stability of the system under the composite controller. Finally, numerical simulation results illustrate the effectiveness of the proposed approach.

Mechanism analysis and structural design of parallel-driven hydraulic wrist joint

Purpose This study aims to design a novel 3 degree-of-freedom parallel-driven hydraulic wrist (PHW) joint, characterized by a compact structure, heavy payload capacity and spherical workspace. Design/methodology/approach In this paper, the kinematics and dynamics mathematical model of PHW is analyzed based on the closed-loop vector method, screw theory and virtual work principle. And the key parameters of PHW are determined based on the singularity analysis. The integrated design method of hydraulic and mechanical systems is used, thereby enabling a hose-less configuration that fosters a low-leakage hydraulic system structure with reduced self-weight. Additionally, this research proposed a dynamic nonlinear compensation control methodology predicated on a payload model to enhance the stability and precision of trajectory tracking for PHW. Finally, several experiments have been conducted to evaluate and validate the performance of the proposed approach and the payload capacity of PHW. Findings Experiment results show that PHW has a payload-to-self-weight ratio of 4(payload 14 kg with self-weight 3.5 kg) under supply pressure 7 MPa. The experimental assessment of payload capacity substantiates the efficacy of the dynamic nonlinear compensation control method for PHW. Remarkably, the trajectory tracking errors for PHW remain under 0.03 rad, even when subjected to payloads of 10.5 and 14 kg. Originality/value This study presents an effective parallel hydraulic-driven wrist structure. This parallel structure provides a spherical workspace with flexible motion, and larger payload capacity compared with the existing robot wrist.

Effect of Weed Management Practices on Citrus Growth and Cost of Production at Young Mandarin Orchard in Palpa, Nepal

ABSTRACT Although citrus cultivation has a comparative advantage in subtropical climates, meeting the increasing demand is challenging, primarily due to weed pressure contributing 25–33% yield loss. Henceforth, to assess the efficiency of weed management methods, enhance plant growth, and analyze economic treatment costs, research was conducted in a three-year-old mandarin (Citrus reticulata Blanco.) orchard at Citrus Development Center, Tansen, Palpa, in 2022. The experiment was designed in a single factorial randomized complete block design with five treatments: plastic mulch, organic mulch, herbicide, hand weeding, and a control. Fourteen weed species were identified, and the highest weed density was of sedges (45%). Results of the study showed that plastic mulch was an efficient method providing lower average weed diversity (1.7); weed density in all days after treatment (DAT) (0.5, 0.6, 1.9, 6.6, and 1.1 m−2); and weed dry weight at 15, 30, and 45 DAT (0.1, 0.3, and 0.4 gm−2). Plastic mulch observed with higher weed control efficiency (93.9, 87.1, 93.1, 91.8, and 93.4%) and weed control index (89.6%, 85.8%, 93.8%, 90.8%, and 96.35%) in all DAT. Whereas, the weed persistence index was lower in herbicide-treated plots at 30 (0.73), 45 (0.44), and 75 (0.24) DAT. Herbicide-treated plots showed the highest increment in crop growth parameters of plant height (33.7%) and plant canopy cover volume (180.8%) and were also the most economical with the lower annual treatment cost (NPR 210 thousand/ha). The superior plant growth, higher weed control, and lower cost proved herbicide treatment as an effective weed control method. However, plastic mulch, with outcomes resembling herbicide, can be a sustainable approach for weed control.

Research on Tightening Technique of Turbopump Shaft System Based on Elongation Method

As the key role of turbopumps in spacecraft engines becomes increasingly prominent, accurate control of their shaft system tightening force is significant to ensure the stable operation of the engines. Although the traditional torque method has been widely used in the tightening of threaded connections, the tightening force is easily affected by the quality of threads and lubrication conditions, and the accuracy and consistency are poor. This paper investigates the elongation method based on the turbopump shaft system tightening force control method. It is applied to the turbopump rotor assembly scenario for the first time. The performance of the torque and elongation methods under different thread qualities and lubrication conditions is compared through experiments. The experimental results show that the elongation method has significant advantages in improving the consistency and accuracy of the tightening force, especially under poor thread fit or different lubrication conditions.

A Novel Reinforcement Learning Algorithm-Based Control Strategy for Grid-Configured Inverters

To address the power oscillation problem due to the introduction of inertia and damping, this paper proposes a new deep reinforcement learning algorithm based on the SD3 (Softmax Deep Double Deterministic policy gradients) algorithm for grid configuration inverter control strategy to compensate for the loss of inertia and damping in the grid. Virtual synchronous generator control, as a typical grid configuration technique, inevitably brings stability problems while providing inertia and damping support to the grid. In this paper, we first analyze the nonlinear relationship between inertia and angular velocity, and find the key parameters to maintain the power stability; then, we migrate the deep reinforcement learning strategy, and design the control strategy applicable to the virtual synchronous generator; finally, through the adaption of the key parameters, we combine the control strategy with the grid-connected inverter, and solve the problem of the excessive grid-connected power oscillation of the inverter. The effectiveness and accuracy of the control method compared with other algorithms are verified by building a simulation model in MATLAB/Simulink, which realizes the purpose of reducing power oscillation.

Research on Optimized Multi‐Objective FCS‐MPC Without Weighting Factors of NPC Three‐Level Inverter

ABSTRACTTo address a series of issues in the application of finite control set model predictive control (FCS‐MPC) strategy for neutral point clamped (NPC) three‐level inverters, such as large amount of rolling optimization calculation, poor midpoint voltage balance effect, high common mode voltage, and complex design of weighting coefficients, this paper proposes an optimized multi‐objective FCS‐MPC strategy without weighting factors. First, the method applies the idea of space vector region division, to obtain the optimal region based on Lyapunov function, and combines with delay compensation, reducing the system's optimization time and enhancing the control precision of the system. Second, aiming at the issue of multi‐objective control for inverters, by constructing the objective function to control tracking reference current, midpoint voltage balance, and reduce common mode voltage, a hierarchical optimization control method is adopted. This approach eliminates the need to design complex weighting coefficients constrained in the objective function as constraints, thereby improving the accuracy of predicted currents. Finally, the optimized multi‐objective FCS‐MPC control strategy is validated through simulation and experimentation to achieve a better balance of midpoint voltage and reduce common mode voltage and harmonic content, thereby enhancing the control precision and dynamic/static performance of the system.

Targeted cattle grazing for shrub control in woody‐encroached oak savannas

Woody encroachment threatens savanna ecosystems around the world. In the midwestern United States, remnant oak savannas persist in a woody‐encroached state due to the removal of grazing and fire disturbances from the landscape. Primary oak savanna restoration methods, such as thinning and fire, can promote a dense shrub layer. Therefore, it is necessary to explore other tools to control woody species, such as targeted grazing. We conducted an experiment to evaluate the effectiveness of targeted cattle grazing as a shrub control method and its impacts on the herbaceous community. We used high‐density, short‐duration grazing to target shrubs and minimize negative non‐target impacts. We found that this type of cattle management reduced shrub density over the short term, but there was substantial resprout after 1 year of no grazing. Targeted grazing lowered herbaceous cover and shifted species composition but did not affect herbaceous species richness or diversity. We saw no increase in non‐native cover during the study, though we documented isolated occurrences of new non‐native species in the grazing paddocks. Overall, our study points to the potential of targeted cattle grazing as a viable tool to help restore the understory of woody‐encroached ecosystems. Successfully meeting vegetation objectives requires a grazing manager with knowledge of the site, the target species, and livestock care and nutrition, as well as a commitment to adaptive management.

Pulse engineering via projection of response functions

We present an iterative optimal control method of quantum systems, aimed at an implementation of a desired operation with optimal fidelity. The update step of the method is based on the linear response of the fidelity to the control operators, and its projection onto the mode functions of the corresponding operator. Our method extends methods such as gradient-ascent pulse engineering (GRAPE) and variational quantum algorithms, by determining the fidelity gradient in a hyperparameter-free manner, and using it for a multiparameter update, capitalizing on the multimode overlap of the perturbation and the mode functions. This directly reduces the number of dynamical trajectories that need to be evaluated in order to update a set of parameters. We demonstrate this approach, and compare it to the standard GRAPE algorithm, for the example of a quantum gate on two qubits, demonstrating a clear improvement in convergence and optimal fidelity of the generated protocol. Published by the American Physical Society 2025

Count-rate management in 131I SPECT/CT calibration

BackgroundSystem calibration is essential for accurate SPECT/CT dosimetry. However, count losses due to dead time and pulse pileup may cause calibration errors, in particular for 131I, where high count rates may be encountered. Calibration at low count rates should also be avoided to minimise detrimental effects from e.g. background counts and statistical fluctuations. This paper aims to present experimental data illustrating count-rate dependencies and to propose practical routines to mitigate errors in the 131I calibration procedure without needing advanced analysis tools.ResultsThe sensitivities of two General Electric (GE) Discovery 670 Pro systems were assessed using two Jaszczak phantom geometries. SPECT/CT data were collected over two months, starting with an initial 131I content of > 2 GBq, decaying to approximately 20 MBq. This allowed for a detailed analysis of count losses due to dead time and pulse pileup. From the sensitivity analysis, it was shown that robust calibration was obtained for 131I phantom activities ranging between 250 and 1500 MBq.ConclusionsThe results show that adequate corrections for dead-time and pulse-pileup counting losses are essential for accurate calibration. It is argued that loss corrections should be based on total spectrum count rates in projections and not only on the 364.5 keV energy window data. The measurement campaigns presented in this paper, using basic tools and equipment, may serve as a model for establishing routines for count-loss corrections as well as for system calibration and regular control of system sensitivity. The data suggest that analysis of source and count concentration in a homogeneous Jaszczak phantom offers robust calibration, whereas analysis of source strength and counts in a delineated phantom insert offers a practical and robust method for regular quality control.

Sustainability Benefit Evaluation and Optimization of Rural Public Spaces Under Self-Organization Theory

Agriculture-oriented rural areas represent one of the forms of specialized agricultural practices and economic development. Public spaces serve as critical carriers within the rural spatial system. Rural public spaces are divided into two forms: explicit spaces and implicit spaces. The interaction between these forms significantly influences the morphological evolution of rural public spaces. This study takes the ancient village cluster in Anyi, Nanchang City, China as a case study. By collecting POI (Point of Interest) data and conducting surveys on visitors’ landscape preferences, it employs a life circle spatial division method and the VEISD (Village Evaluation Indicators for Sustainable Development) entropy model to evaluate the sustainability benefits of rural public spaces. Based on the evaluation results, the study proposes a control and guidance method for public spaces under self-organization theory. This method leverages the interference effects of explicit rural public spaces on implicit spaces to optimize rural public spaces. The study focuses on the planning and renovation of public space nodes in Luotian Village. By adjusting the sub-indicator “Village Public Environment Construction D22”, it validates the scientific robustness of the systems analysis theory and the VEISD framework. By adjusting the spatial layout and attributes of a critical spatial node—the Ancient Camphor Tree Square in Luotian Village—within rural public space planning, the study advances the guidance and control of public spaces during the self-organization evolution of rural areas. It enhances the openness of spatial forms and the functional integration of public space nodes. The results demonstrate that this method can analyze the vitality characteristics of factors within subsystems through the layout and indicator system of rural public spaces. It also validates the findings via correlation tests with the demands for POI and landscape preferences, ultimately constructing the VEISD framework for rural public spaces. This research provides theoretical support for optimizing the resource transformation and utilization of rural public spaces, offering a reference model for the sustainable development of rural areas.

Secure Control of Networked Control Systems Under Replay Attacks: A Switching‐Like Approach

ABSTRACTThis paper focuses on the secure control design of networked control systems (NCSs) under replay attacks. Mitigating replay attacks is a challenging task since the statistical similarity between replayed signals and real observations makes them difficult to distinguish. Given the persistence of potential attackers and the probability of individual attack failures, a novel switching‐based replay attack model is introduced. By employing this replay attack model, NCSs vulnerable to replay attacks can be transformed into a class of switching‐like systems. Within the framework of the average dwell time switching strategy and multiple Lyapunov stability theory, sufficient conditions for the mean‐square exponential stability of the underlying system are presented. Compared with the existing control schemes using the delay‐based replay attack model, the proposed secure control method effectively reduces the impact of replay attacks on the control performance. The effectiveness of the proposed approach is validated through simulation experiments carried out on two practical systems.

Evaluation of Low‐Pressure Microwave Oxygen Plasma as an Ecofriendly Way to Control Three of the Most Important Pests of Stored Date Fruits Infesting Egyptian Cultivar Siwi

ABSTRACTInsect pests in stored date fruits lead to significant economic losses, traditionally managed by chemical insecticides that harm the environment. This study explores low‐pressure microwave oxygen plasma treatments as an alternative pest control method against pests like Polda interpunctelia, Ephestia cautella, and Oryzaephilus surinamensis. A 20 s treatment achieved 100% mortality for all species without any adult emergence. Sensory evaluations showed no significant differences in taste, color, texture, odor, or overall acceptability between treated and untreated date fruits, indicating that the plasma treatment preserves fruit quality. Scanning electron microscopy revealed structural damage to the pests, whereas the Siwi cultivar date fruits remained unaffected. The findings suggest that this plasma treatment is an effective and environmentally friendly alternative to chemicals.

Collaborative Control of UAV Swarms for Target Capture Based on Intelligent Control Theory

Real-time dynamic capture of a single moving target is one of the most crucial and representative tasks in UAV capture problems. This paper proposes a multi-UAV real-time dynamic capture strategy based on a differential game model to address this challenge. In this paper, the dynamic capture problem is divided into two parts: pursuit and capture. First, in the pursuit–evasion problem based on differential games, the capture UAVs and the target UAV are treated as adversarial parties engaged in a game. The current pursuit–evasion state is modeled and analyzed according to varying environmental information, allowing the capture UAVs to quickly track the target UAV. The Nash equilibrium solution in the differential game is optimal for both parties in the pursuit–evasion process. Then, a collaborative multi-UAV closed circular pipeline control method is proposed to ensure an even distribution of capture UAVs around the target, preventing excessive clustering and thereby significantly improving capture efficiency. Finally, simulations and real-flight experiments are conducted on the RflySim platform in typical scenarios to analyze the computational process and verify the effectiveness of the proposed method. Results indicate that this approach effectively provides a solution for multi-UAV dynamic capture and achieves desirable capture outcomes.

Micro-Assembly Error Control of Specialized MEMS Friction Sensor

A skin friction sensor is a three-dimensional MEMS sensor specially designed for measuring the skin friction of hypersonic vehicle models. The accuracy of skin friction measurement under hypersonic laminar flow conditions is closely related to the fabrication and micro-assembly accuracy of MEMS skin friction sensors. In order to achieve accurate skin friction measurement, high-precision linear laser scanning ranging, multi-axis precision drive, and 3D reconstruction algorithms are investigated; a MEMS skin friction sensor micro-assembly height error measurement system is developed; and the MEMS skin friction sensor micro-assembly height error control method is carried out. The results show that the micro-assembly height error measurement of MEMS skin friction sensors achieves an accuracy of up to 2 μm. The height errors of the MEMS skin friction sensor were controlled within −8 μm to +10 μm after error control. The angular errors were controlled within the range of 0.05–0.25°, significantly improving micro-assembly accuracy in the height direction of the MEMS skin friction sensor. The results of hypersonic wind tunnel tests indicate that the deviation in the accuracy of the MEMS skin friction sensors after applying height error control is about 5%, and the deviation from the theoretical value is 8.51%, which indicates that height error control lays the foundation for improving the accuracy of skin friction measurement under hypersonic conditions.

Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles

Small Autonomous Surface/Underwater Vehicles (S-ASUVs) are gradually attracting attention from related fields due to their small size, low energy consumption, and flexible motion. Existing dynamic positioning (DP) control approaches suffer from chronic restrictions that hinder adaptability to varying practical conditions, rendering performance poor. A new three-dimensional (3D) dynamic positioning control method for S-ASUVs is proposed to tackle this issue. Firstly, a dynamic model for the DP control problem considering thrust allocation was established deriving from dynamic models of S-ASUVs. A novel Lyapunov-based model predictive control (LBMPC) method was then designed. Unlike the conventional Lyapunov-based model predictive control (LMPC), this study used multi-variable proportional–integral–derivative (PID) control as the secondary control law, improving the accuracy and rapidity of the control performance significantly. Both the feasibility and stability were rigorously proved. A series of digital experiments using the S-ASUV model under diverse conditions demonstrate the proposed method’s advantages over existing controllers, affirming satisfactory performances for 3D dynamic positioning in complex environments.

China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control

Water vapor is an active trace component in the troposphere and has a significant impact on meteorology and the atmospheric environment. In order to meet demands for high-precision water vapor and aerosol observations for numerical weather prediction (NWP), the China Meteorological Administration (CMA) deployed 49 Raman aerosol lidar systems and established the first Raman–Mie scattering lidar network in China (CARLNET) for routine measurements. In this paper, we focus on the water vapor measurement capabilities of the CARLNET. The uncertainty of the water vapor Raman channel calibration coefficient (Cw) is determined using an error propagation formula. The theoretical relationship between the uncertainty of the calibration coefficient and the water vapor mixing ratio (WVMR) is constructed based on least squares fitting. Based on the distribution of lidar in regions with different humidity conditions, the method of real-time calibration and quality control based on radiosonde data is established for the first time. Based on the uncertainty requirements of the World Meteorological Organization for water vapor in data assimilation, the calibration and quality control thresholds of the WVMR in regions with different humidity conditions are determined by fitting real-time lidar and radiosonde data. Lastly, based on the radiosonde results, the calibration algorithm established in this study is used to calibrate CARLNET data from October to December 2023. Compared with traditional calibration results, the results show that the stability and detection accuracy of the CARLNET significantly improved after calibration in regions with different humidity conditions. The deviation of the Cw decreased from 12.84~18.47% to 5.41~11.54%. The inversion error of the WVMR compared to radiosonde decreased from 1.05~0.46 g/kg to 0.82~0.34 g/kg. The reliability of the improved calibration algorithm and the CARLNET’s performance have been verified, enabling them to provide high-precision water vapor products for NWP.

Evaluation of Larrea tridentata Extracts and Their Antimicrobial Effects on Strains of Clinical Interest

The use of medicinal plants represents an alternative method for bacterial control due to their chemical compositions. This study’s objective was to determine the inhibitory capacity of Larrea tridentata extracts against microbial strains of clinical interest. Four extracts were prepared, their phytochemical profiles were determined, and their antioxidant capacities were quantified. Additionally, the minimum concentrations of hemolysis were determined using human blood erythrocytes. For the extracts’ growth inhibitory capacity, six bacterial and two fungal strains were evaluated using the disk diffusion test. Commercial medications specific for each strain were used as controls. The ethanolic extracts registered the greatest diversity of metabolites related to antibacterial activity. The inhibitory activities of the ethanolic extract and the Cedax® control were similar for Enterococcus faecalis. A principal component analysis was performed with X2 and ANOVA tests to identify the relationships and the effects of the extracts on bacterial inhibition, obtaining p > 0.05 with a confidence level of 95%. This research highlights the potential of L. tridentata extracts as an alternative treatment and to mitigate the growing problem of resistance to traditional antibiotics.

Nonlinear reference tracking using robust MPC without computing all linearised models

The presence of systems with polytopic disturbances in practice is highlighted through a novel reference tracking control method for nonlinear systems. The main steps are to obtain a polytopic linear difference inclusion description of the nonlinear system by linearising the system around the references to be followed using Taylor linearisation and to apply the proposed robust model predictive control method for systems with polytopic disturbances. Not all linearised models are constructed and the main advantage is that through convex combinations, every linearised model is used in the control law computations. The efficiency of the method is demonstrated in a 3D simulation for an aerial vehicle.