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Development of automatic Cartesian Robot Cannabis Seeder using LabVIEW

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Development of Automatic Cartesian Robot Cannabis Seeder usi...

International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications engineering (ECTI-NCON)

作者： Rujipan Kosarat Keattipoom Sangwai Anan Wongjan Department of Software Engineering Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand Department of Electronic Engineering and Automatic Control Systems Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This article describes the invention of autonomous cannabis seeding equipment to reduce contamination and planting time. The automated cannabis seeder employs an NI myRIO control board to operate a y-axis stepper motor attached to a ball screw to move along the breadth of each row of 14 seed trays. Soil drilling and burial Drill all holes at the same depth. This promotes seed germination and lowers human-seed germ contamination. These 7 soil drill heads and 7 seeders use 3D printers to design and shape the workpiece. An 800-watt air pump smokes the cannabis seeds. Linear electric motors function in two rows in the z-axis. The buffer reverses the drowning process from row 14 to the first row, starting from the 3rd row and continuing through the final series of steps until 14 rows in the y-axis are complete. The hardware controls all program activities in LabVIEW. We tested the automated cannabis seeding machine 100 times on average, sowing cannabis seeds into 98 seed trays and dropping 93 seeds at 94.80% efficiency in 10.38 minutes. A 16 percent faster machine than human work is available.

关键词： Technological innovation Motor drives Shape Soil Pulse width modulation Three-dimensional printing Seeds (agriculture) Printers Robots Contamination

CONVERGENCE ANALYSIS OF LINEARIZED q PENALTY METHODS FOR NONCONVEX OPTIMIZATION WITH NONLINEAR EQUALITY CONSTRAINTS

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arXiv 2025年

作者： El Bourkhissi, Lahcen Necoara, Ion Department of Automatic Control and Systems Engineering National University of Science and Technology Politehnica Bucharest Romania Department of Automatic Control and Systems Engineering National University of Science and Technology Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest050711 Romania

In this paper, we consider nonconvex optimization problems with nonlinear equality constraints. We assume that the objective function and the functional constraints are locally smooth. To solve this problem, we introduce a linearized q penalty based method, where q ∈ (1, 2] is the parameter defining the norm used in the construction of the penalty function. Our method involves linearizing the objective function and functional constraints in a Gauss-Newton fashion at the current iteration in the penalty formulation and introduces a quadratic regularization. This approach yields an easily solvable subproblem, whose solution becomes the next iterate. By using a novel dynamic rule for the choice of the regularization parameter, we establish that the iterates of our method converge to an ǫ-first-order solution in O(1/ǫ2+(q−1)/q) outer iterations. Finally, we put theory into practice and evaluate the performance of the proposed algorithm by making numerical comparisons with existing methods from literature. © 2025, CC BY.

关键词： Numerical methods

Enhancing Thin-Film Wafer Inspection With A Multi-Sensor Array And Robot Constraint Maintenance

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arXiv 2025年

作者： Sánchez-Arriaga, Néstor Eduardo Canzini, Ethan Espley-Plumb, Nathan John Farnsworth, Michael Pope, Simon Leyland, Adrian Tiwari, Ashutosh Department of Automatic Control & Systems Engineering University of Sheffield Sheffield United Kingdom Department of Materials Science & Engineering University of Sheffield Sheffield United Kingdom Airbus Robotics Airbus UK Chester United Kingdom

Thin-film inspection on large-area substrates in coating manufacture remains a critical parameter to ensure product quality;however, extending the inspection process precisely over a large area presents major challenges, due to the limitations of the available inspection equipment. An additional manipulation problem arises when automating the inspection process, as the silicon wafer requires movement constraints to ensure accurate measurements and to prevent damage. Furthermore, there are other increasingly important large-area industrial applications, such as Roll-to-Roll (R2R) manufacturing where coating thickness inspection introduces additional challenges. This paper presents an autonomous inspection system using a robotic manipulator with a novel learned constraint manifold to control a wafer to its calibration point, and a novel multi-sensor array with high potential for scalability into large substrate areas. We demonstrate that the manipulator can perform required motions whilst adhering to movement constraints. We further demonstrate that the sensor array can perform thickness measurements statically with an error of 0.5◦ from the calibration point whilst monitoring the RMSE and R2 over 1406 data points. These features are potentially useful for detecting displacement variations in R2R manufacturing processes. © 2025, CC BY-NC-ND.

关键词： Silicon wafers

An ANN-Enhanced Approach for Flatness-Based Constrained control of Nonlinear systems

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arXiv 2025年

作者： Do, Huu-Thinh Prodan, Ionela Stoican, Florin Univ. Grenoble Alpes Grenoble INP LCIS ValenceF-26000 France Institute of Engineering and Management University Grenoble Alpes France Department of Automatic Control and Systems Engineering UPB Romania

Neural networks have proven practical for a synergistic combination of advanced control techniques. This work analyzes the implementation of rectified linear unit neural networks to achieve constrained control in differentially flat systems. Specifically, the class of flat systems enjoys the benefit of feedback linearizability, i.e., the systems can be linearized by means of a proper variable transformation. However, the price for linearizing the dynamics is that the constraint descriptions are distorted geometrically. Our results show that, by using neural networks, these constraints can be represented as a union of polytopes, enabling the use of mixed-integer programming tools to guarantee constraint satisfaction. We further analyze the integration of the characterization into efficient settings such as control Lyapunov function-based and model predictive control (MPC). Interestingly, this description also allows us to explicitly compute the solution of the MPC problem for the nonlinear system. Several examples are provided to illustrate the effectiveness of our framework. © 2025, CC BY-NC-ND.

关键词： Mixed-integer linear programming

Multi-agent Collision Avoidance Based on Buffered Voronoi Cells and B-Splines

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Multi-agent Collision Avoidance Based on Buffered Voronoi C...

16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： Dinh, Cong Khanh Prodan, Ionela Stoican, Florin LCIS Valence26000 France Department of Automatic Control and Systems Engineering National University of Science and Technology "Politehnica" Bucharest 313 Splaiul Independenţei Bucharest060042 Romania

ISBN: (纸本)9783031817236

This paper tackles the challenging issue of collision avoidance among multiple dynamical agents, a problem known for its non-convex nature and computational complexity. Our proposed solution involves decomposing the space into time-varying Voronoi cells with buffer zones, exploiting the versatility of B-splines to reconfigure trajectories when collisions are predicted. This approach is integrated into a Model Predictive control (MPC) framework, implemented in a distributed manner where agents communicate predicted control point sequences defining the B-spline curves. Through simulation testing across various scenarios, our approach demonstrates significant promise, paving the way for experimental validation and real-world applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems

Vibration Mitigation of Hybrid Oscillating Water Column-Floating Offshore Wind Turbine Using ANFIS-Based Airflow control

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Vibration Mitigation of Hybrid Oscillating Water Column-Floa...

16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： M’zoughi, Fares Aboutalebi, Payam Ahmad, Irfan Rouch, Tahereh Bagheri Garrido, Izaskun Garrido, Aitor J. De La Sen, Manuel Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Po Rafael Moreno no. 3 Bilbao48013 Spain Automatic Control Group—ACG Institute of Research and Development of Processes IIDP Department of Electricity and Electronics Faculty of Science and Technology University of the Basque Country—UPV/EHU Bo Sarriena s/n Leioa48080 Spain

ISBN: (纸本)9783031817236

This paper introduces a novel approach to model and stabilize a Floating Offshore Wind Turbine (FOWT) by employing Oscillating Water Columns (OWC) as an active structural control system. The innovative concept involves designing a new floating barge-like platform with integrated OWCs on opposite sides of the platform to mitigate undesired oscillations of the system. These OWCs counteract the bending forces caused by wind on the tower and waves on the barge platform. To synchronize the opposing forces with the system’s tilting, a proposed Adaptive Neuro-Fuzzy Inference System-based airflow control strategy is employed. Through manipulation of the barge platform’s pitch angle, the ANFIS airflow control system adjusts the valves on either side, opening one and closing the other accordingly. Simulation results, compared with a standard FOWT demonstrate the effectiveness of the ANFIS airflow control. It is shown to be superior in reducing platform pitching and the fore-aft translation of the tower top. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Active Structural control Air Valve Airflow control ANFIS Barge Platform Floating Offshore Wind Turbine Oscillating Water Column

Path planning with moving obstacles using stochastic optimal control

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arXiv 2025年

作者： Jafari, Seyyed Reza Hansson, Anders Wahlberg, Bo Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-581 83 Sweden Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

Navigating a collision-free, optimal path for a robot poses a perpetual challenge, particularly in the presence of moving objects such as humans. In this study, we formulate the problem of finding an optimal path as a stochastic optimal control problem. However, obtaining a solution to this problem is nontrivial. Therefore, we consider a simplified problem, which is more tractable. For this simplified formulation, we are able to solve the corresponding Bellman equation. However, the solution obtained from the simplified problem does not sufficiently address the original problem of interest. To address the full problem, we propose a numerical procedure where we solve an optimization problem at each sampling instant. The solution to the simplified problem is integrated into the online formulation as a final-state penalty. We illustrate the efficiency of the proposed method using a numerical example. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

Immersive Virtual Reality Cruise Garden Relaxation Train: A Novel BCI Platform for Depression 6th

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Immersive Virtual Reality Cruise Garden Relaxation Train: A ...

6th International Conference on Biomedical and Health Informatics, ICBHI 2024

作者： Tsai, Shu-Hui Chao, Chih-Chiang Lin, Yue-Der Kuo, Chin-Jung Dong, Shu-Ping Liu, Chun-Yuan Ko, Hsin-Yi Wang, Jenn-Hann Liu, Ching Hsiu Service Systems Technology Center Industrial Technology Research Institute Hsin-Chu Taiwan Center for Measurement Standards Industrial Technology Research Institute Hsin-Chu Taiwan Department of Automatic Control Engineering Feng-Chia University Taichung Taiwan Central Division Industrial Technology Research Institute Hsin-Chu Taiwan Mackay Memorial Hospital Hsin-Chu Taiwan

ISBN: (纸本)9783031863226

The staggering global prevalence of depression extends to Taiwan, where approximately 8.9% of the population exhibits symptoms of depression, affecting around 2 million individuals, with 1.25 million classified as severe cases. Depression exerts profound impacts on both socioeconomic and health aspects, ranking as one of the leading causes of disability and closely linked with dementia. Over 70% of suicides involve individuals with depression, and those with depression face significantly higher suicide risks compared to the general population. Of particular concern is the higher-than-expected prevalence of depression, which, if left untreated, may escalate suicide risks. Research indicates that individuals with depression display unstable and imbalanced brainwave patterns, characterized by a lack of normal baseline brainwaves and elevated slow waves. While the commonly used repeated transcranial magnetic stimulation (rTMS) therapy can modulate brainwaves, the treatment is costly and often associated with high relapse rates, imposing a significant burden on patients. Recent studies reveal that potential depression sufferers commonly experience brainwave dysregulation and neuro-immune disruption, emphasizing the need for personalized emotional, brainwave, and autonomic nervous system regulation, along with community support. This study aims to integrate elements such as "Brainwave Entrainment with Schumann Resonance and Autonomic Nervous System Feedback Device", "Light Therapy Device", and "Garden Train-Style Anxiety-Relief Environment" to provide simulated natural environment brainwave and autonomic nervous system regulation, as well as light therapy. Additionally, it involves designing a safe "Garden Train" virtual reality environment to offer a secure and comforting anxiety-relief space for individuals at risk or suffering from depression, as well as caregivers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electrotherapeutics

System Identification Beyond the Nyquist Frequency: A Kernel-Regularized Approach

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arXiv 2025年

作者： van Haren, Max Smith, Roy S. Oomen, Tom Department of Mechanical Engineering Control Systems Technology Section Eindhoven University of Technology Groene Loper 5 Eindhoven5612 AE Netherlands Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland Delft Center for Systems and Control Delft University of Technology Mekelweg 2 Delft2628 CN Netherlands

Models that contain intersample behavior are important for control design of systems with slow-rate outputs. The aim of this paper is to develop a system identification technique for fast-rate models of systems where only slow-rate output measurements are available, e.g., vision-in-the-loop systems. In this paper, the intersample response is estimated by identifying fast-rate models through least-squares criteria, and the limitations of these models are determined. In addition, a method is developed that surpasses these limitations and is capable of estimating unique fast-rate models of arbitrary order by regularizing the least-squares estimate. The developed method utilizes fast-rate inputs and slow-rate outputs and identifies fast-rate models accurately in a single identification experiment. Finally, both simulation and experimental validation on a prototype wafer stage demonstrate the effectiveness of the framework. © 2025, CC BY-NC-ND.

关键词： Decentralized systems