Multilayer Control Research Articles

An Extended Study of the Performance of Flexible Controllers Composed of Micro-controllers

Generic controllers for self-adaptive systems can be configured parametrically according to system needs, even though their reuse is restricted because of the wide range of services that may be provided by each stage of a feedback control loop, like MAPE-K. Rainbow is a typical example of such a generic, monolithic controller. This article revisits and extends prior work that advocates structurally flexible controllers, as ensembles of micro-controllers each providing specific services. We experimented with our approach with three different architectural configurations for the controller: monolithic, decentralised, and decentralised with a meta-controller. Our results indicate that despite the decentralised configuration with a meta-controller demanding more computational resources, it performed comparatively well compared to the other configurations, including when measuring the target system’s response time. Moreover, we found that variations of the control loop timing at the different layers of the controller impact the stability of the target system. We have also evolved the controller by adding a new micro-controller, which caused no impact on the other micro-controllers, and mostly kept the target system’s performance. We conclude that a multi-layered controller design, based on micro-controllers, provides the basis for defining structurally flexible controllers at operational-time, and may promote reuse at development-time.

Chemo-optogenetic Dimerization Dissects Complex Biological Processes.

Light offers superior control in terms of high temporal precision, high spatial precision, and non-invasiveness for the regulation of cellular functions. In recent years, chemical biologists have adopted chemo-optogenetic dimerization approaches, such as photo-triggered chemical inducers of dimerization (pCIDs), as a general tool for spatiotemporal regulation of cellular functions. Traditional chemo-optogenetic dimerization triggers either a single ON or a single OFF of cellular activity. However, more sophisticated approaches are introduced in recent years. These include the ability to turn ON and OFF using different wavelengths of light, tools enabling multi-layer control of cellular activities, and nanobody-tethered photodimerizers. These advancements not only shed light on the study of ubiquitously existing multi-functional proteins but also create new opportunities for investigating complex cellular activity networks.

Quantitative RNA pseudouridine maps reveal multilayered translation control through plant rRNA, tRNA and mRNA pseudouridylation.

Pseudouridine (Ψ) is the most abundant RNA modification, yet studies of Ψ have been hindered by a lack of robust methods to profile comprehensive Ψ maps. Here we utilize bisulfite-induced deletion sequencing to generate transcriptome-wide Ψ maps at single-base resolution across various plant species. Integrating ribosomal RNA, transfer RNA and messenger RNA Ψ stoichiometry with mRNA abundance and polysome profiling data, we uncover a multilayered regulation of translation efficiency through Ψ modifications. rRNA pseudouridylation could globally control translation, although the effects vary at different rRNA Ψ sites. Ψ in the tRNA T-arm loop shows strong positive correlations between Ψ stoichiometry and the translation efficiency of their respective codons. We observed a general inverse correlation between Ψ level and mRNA stability, but a positive correlation with translation efficiency in Arabidopsis seedlings. In conclusion, our study provides critical resources for Ψ research in plants and proposes prevalent translation regulation through rRNA, tRNA and mRNA pseudouridylation.

Multi-layer access control for cloud data using improved DBSCAN, AES, homomorphic encryption, and RMAAC for text, image, and video

Multi-layer access control for cloud data using improved DBSCAN, AES, homomorphic encryption, and RMAAC for text, image, and video

Multi-layer process control in selective laser melting: a reinforcement learning approach

AbstractPowder bed fusion (PBF) is an original additive manufacturing technique for creating 3D parts layer-by-layer. While there are numerous benefits to this process, the complex undergoing physical phenomena are challenging to analytically model and interpret. Hence, integrated and control-oriented 3D models are lacking in the current literature. As a result, the state of the art in process control for the powder bed fusion (PBF) process is not as advanced as in other manufacturing processes. Reinforcement learning is a machine learning, data-driven mathematical and computational framework that can be used for process control while addressing this challenge (lack of control-oriented models) effectively. Its flexible formulation and its trial-and-error nature make reinforcement learning suitable for processes where the model is intricate or even unknown. The focus of this research work is selective laser melting, which is a laser-based PBF process. For the first time in the literature we demonstrate the benefits of a reinforcement learning process control framework for multiple layers (complete 3D parts) and we highlight the importance of stability during training. The presented case studies confirm the effectiveness of the proposed control framework, directly addressing heat accumulation issues while demonstrating effective overall process control, hence opening up opportunities for further research and impact in this area.

Multi-Layered Interactive Target Guidance with Visual Safety in Convex-Shaped Obstacle Environments

In this paper, we consider a control architecture for a mobile robot equipped with visual sensors to pursue a target object in an environment with convex-shaped obstacles. The pursuit involves crucial occlusion avoidance and field of view maintenance, referred to as visual safety. Our goal is to achieve this safety through a multi-layered control architecture consisting of a planning layer and a safety layer. We propose functions that represent occlusion avoidance and field of view maintenance and derive conditions for these to act as control barrier functions. Utilizing these functions, we implement an optimal control at the planning layer and an optimization-based control at the safety layer. The effectiveness of this method is verified through two tasks: guiding the target object into a target location and preventing the target object from entering a target location.

Dynamic damage law and failure modes of layered coal-rock mass under impact loading

Abstract Up to now, most of the structural dynamic analysis is based on the Lagrange system, while the Hamilton system is composed of the phase space composed of the generalized displacement and stress, showing a wonderful symmetry, which opens up a new way for the theoretical research and calculation of dynamics. The physical model of the layered combined coal-rock is constructed by dividing the ‘outburst center’ coal in front of the heading face into the combined layered structure. Based on Hamilton mechanics, the Hamilton canonical equation under symplectic geometry structure is established, combined with Hamilton variational principle and symplectic time subdomain method, the multi-layer symplectic element control equation of coal-rock is established, and the dynamic displacement and stress transfer characteristics at any time can be solved by iterative calculation. The action modes of axial torsional stress, radial principal stress and shear stress of layered coal- rock under impact loading are determined, and the weak layer and interlayer stress transfer dynamic response behavior of layered coal- rock under complex stress conditions are determined. The conclusions are as follows: ①Under static loading, the layered shear stress circle provides the initial condition of damage failure, impact loading acts as an exciting force to trigger the torsion effect, forming the ‘ X ’ -shaped shear line in the radial and axial directions of the interlayer interface, and the boundary produces the ‘ V ’ -shaped dynamic spalling surface. ②The short axis is damaged before the long axis, and the central node is the starting point of instability. The main cracks are formed along the long and short axis respectively, and finally the ‘ O-+ ’ failure mode is formed, which verifies the prominent axial and radial spallation phenomenon. This method avoids the non-conservation of system energy caused by energy dissipation, and will become an effective method to study the dynamic mechanical properties and damage evolution path of coal-rock. It has guiding and reference significance for the theoretical research and prevention technology of coal and rock dynamic disasters.

Exploring the methyl-verse: Dynamic interplay of epigenome and m6A epitranscriptome.

The orchestration of dynamic epigenetic and epitranscriptomic modifications is pivotal for the fine-tuning of gene expression. However, these modifications are traditionally examined independently. Recent compelling studies have disclosed an interesting communication and interplay between m6A RNA methylation (m6A epitranscriptome) and epigenetic modifications, enabling the formation of feedback circuits and cooperative networks. Intriguingly, the interaction between m6A and DNA methylation machinery, coupled with the crosstalk between m6A RNA and histone modifications shape the transcriptional profile and translational efficiency. Moreover, m6A modifications interact also with non-coding RNAs, modulating their stability, abundance, and regulatory functions. In the light of these findings, m6A imprinting acts as a versatile checkpoint, linking epigenetic and epitranscriptomic layers toward a multilayer and time-dependent control of gene expression and cellular homeostasis. The scope of the present review is to decipher the m6A-coordinated circuits with DNA imprinting, chromatin architecture, and non-coding RNAs networks in normal physiology and carcinogenesis. Ultimately, we summarize the development of innovative CRISPR-dCas engineering platforms fused with m6A catalytic components (m6A writers or erasers) to achieve transcript-specific editing of m6A epitranscriptomes that can create new insights in modern RNA therapeutics.

A multilayer control architecture for greenhouse crop production in agro-industrial districts: Conceptual framework, prospects and challenges

Agriculture is one of the most important primary-industry sectors, in which automatic control plays a crucial role in ensuring sustainability. This paper presents a conceptual view for a greenhouse control architecture that merges past and present technological trends. The main prospects and challenges are described, considering not only aspects of crop production but also other issues related to fruit quality, the environment, resource-use efficiency within the energy-water-food nexus, and IoT-based solutions. Illustrative results are shown for the different layers of the architecture, focusing on process control and optimal resource dispatch for an experimental case using a real Mediterranean greenhouse that is part of an agro-industrial district also comprising a solar desalination plant and multiple auxiliary systems. These results contribute to understanding the different techniques and paradigms employed, and their consequent advantages and disadvantages.

Static pinning synchronization control of self-triggered coupling dynamical networks

In this paper, a new static pinning intermittent control based on resource awareness triggering is proposed. A multi-layer control technique is used to synchronize the coupled neural network. First, a hierarchical network structure including pinned and interaction layers is induced using each pinning strategy. Second, using the ideas of average aperiodic intermittent control (AIC) rate method and constructing an auxiliary function, a new lemma is proposed for the pinning intermittent synchronization of coupled networks, where the upper/lower bound restrictions on each control width for AIC are relaxed. Third, to obtain the desired synchronization behavior, a self-triggering mechanism (STM) is proposed to execute the AIC of the pinned and interaction layers. Moreover, the proposed STM is effective for the actuation of the static pinning impulsive control. The static pinning method modifies the single pinning and switching pinning impulsive control. Finally, the proposed results are applied to Chua’s circuits, oscillators and small-world networks. Experimental results show the performance of the proposed STM which reduces 34.58% the number of control updates compared to a periodically intermittent event-triggered scheme. Further, for large-scale coupled networks, the N-dimensional Laplacian matrix LV can be decomposed into sp×sp and N−sp×N−sp dimensions by hierarchical method, thus reducing the complexity of calculation.

Optimization and control of robotic vertebral plate grinding: Predictive modeling, parameter optimization, and fuzzy control strategies for minimizing bone damage in laminectomy procedures.

During the robotic grinding of vertebral plates in high-risk laminectomy procedures, programmed operations may inadvertently induce force or temperature-related damage to the bone tissue. Therefore, it is imperative to explore a control methodology aimed at minimizing such damage during the robotic grinding of vertebral plate cortical bone, contingent upon optimal grinding parameters. Initially, predictive models for both the grinding force and temperature of vertebral plate cortical bone were developed using the response surface design (RSD) methodology. Subsequently, employing the satisfaction function approach, multi-objective parameter optimization of these predictive models was conducted to ascertain the optimal combination of parameters conducive to low-damage grinding. The optimum grinding parameters identified were a speed of 6000 r/min, a depth of grind of 0.4 mm, and a feed rate of 3.8 mm/s. Moreover, a multi-layer adaptive fuzzy control strategy was devised, and a corresponding multi-layer adaptive fuzzy controller (MFLC) was then implemented to dynamically adjust the grinding feed speed. The efficacy of this control module was corroborated through Simulink simulations. Simulation results demonstrated that the magnitude of the grinding force fluctuated within the range of 2.2-2.6 N after FLC control, while the fluctuation range of the grinding force was limited to 2.2-2.48 N after MFLC control. This indicates that MFLC control brings the force closer to the target expectation value of 2.39 N compared with FLC control. Finally, the dynamic fuzzy control method predicated on optimal grinding parameters was validated through experimental porcine spine grinding conducted on a robotic vertebral plate grinding platform.

Dynamic multilayered control of m6A RNA demethylase activity

Similar to DNA and histone, RNA can also be methylated. In its most common form, a N6-methyladenosine (m6A) chemical modification is introduced into nascent messenger ribonucleic acid (mRNA) by a specialized methyltransferase complex and removed by the RNA demethylases, Fat mass and obesity-associated (FTO), and ALKBH5. The fate of m6A-marked mRNA is uniquely diverse, ranging from degradation to stabilization/translation, which has been suggested to be largely dependent on its interaction with the family of YT521-B homology (YTH) domain-containing proteins. Here, we highlight a series of control levers that impinge on the RNA demethylases. We present evidence to indicate that intermediary metabolism and various posttranslation modifications modulate the activity, stability, and the subcellular localization of FTO and ALKBH5, further dispelling the notion that m6A methylation is not a dynamic process. We also discuss how examination of these underappreciated regulatory nodes adds a more nuanced view of the role of FTO and ALKBH5 and should guide their study in cancer and nonmalignant conditions alike.

Primed to persevere: Hypoxia regulation from epigenome to protein accumulation in plants.

Plant cells regularly encounter hypoxia (low-oxygen conditions) as part of normal growth and development, or in response to environmental stresses such as flooding. In recent years, our understanding of the multi-layered control of hypoxia-responsive gene expression has greatly increased. In this Update, we take a broad look at the epigenetic, transcriptional, translational, and post-translational mechanisms that regulate responses to low-oxygen levels. We highlight how a network of post-translational modifications (including phosphorylation), secondary messengers, transcriptional cascades, and retrograde signals from the mitochondria and endoplasmic reticulum (ER) feed into the control of transcription factor activity and hypoxia-responsive gene transcription. We discuss epigenetic mechanisms regulating the response to reduced oxygen availability, through focussing on active and repressive chromatin modifications and DNA methylation. We also describe current knowledge of the co- and post-transcriptional mechanisms that tightly regulate mRNA translation to coordinate effective gene expression under hypoxia. Finally, we present a series of outstanding questions in the field and consider how new insights into the molecular workings of the hypoxia-triggered regulatory hierarchy could pave the way for developing flood-resilient crops.

ADRC-Based cooperative control for unmanned towing operation by multiple DP tugboats: A comparative study of two cooperative controllers

This paper addresses the challenge of coordinated manipulation of an unactuated floating object by multiple tugboats to execute both positioning and towing operation within complex marine environments. We proposes a multi-layer cooperative control algorithm for the multi-tugboat system, including tugboat control level and cooperative control level. At the individual tugboat control level, the dynamic positioning system (DPS) has been enhanced to match the operational behavior of the tugboat, enabling it to handle cable tension and environmental disturbances during transit. The controller incorporates a simple yet effective linear active disturbance rejection control method (ADRC) to counter external disturbances and ensure accurate trajectory tracking without relying on preset models. Moving to the multi-tugboat collaboration level, two distinct control strategies are proposed for towing operations: formation-based (FB) and force-allocation-based (FAB). The FB strategy involves multiple tugboats forming a coordinated formation, with control focused on the formation center to indirectly manipulate the object. On the other hand, the FAB strategy utilizes model predictive control (MPC) for the object to allocate the necessary towing force for each cable, thereby determining the required actions for each tugboat based on the cable model and the needed towing force. Simulation results demonstrate that both control strategies can effectively maneuver the floating object with high accuracy to perform positioning and towing tasks. Nevertheless, due to the variations in their fundamental mechanisms, there are significant discrepancies in towline tension, tugboat utilization, and energy consumption.

Multilayer neuroadaptive constraint-handling control architecture for a family of nonlinear systems with uncertainty compensation

In practical applications, there are some requirements for time-varying constraints on full system states. Currently, Barrier Lyapunov Function is a popular tool for constraint control. However, how to handle various uncertainties while satisfying constraint requirements is worth further research. Accordingly, a high-performance multilayer neuroadaptive constraint-handling controller for a class of nonlinear systems with uncertainty compensation will be developed. Significantly, asymmetric time-varying constraints for full system states can be implemented. Furthermore, a set of novel multilayer neuroadaptive disturbance observers will be proposed to address modeling uncertainties. Moreover, by introducing a set of nonlinear command filters, the intelligent control algorithm will be designed via the command filtered backstepping method. The stability of the whole closed-loop system is strictly proved. Additionally, the proposed algorithm is applied to different nonlinear systems including a hydraulic robotic manipulator system to verify its feasibility.

Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System

This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberger observer is designed for state estimation by employing a modified back-propagation algorithm. The proposed observer’s adaptive nature aids in mitigating the impact of noise, disturbance, and parameter variations, which are usually not considered by conventional observers. Based on the observed states, a nonlinear dynamic inversion-based fast terminal sliding mode controller is designed to attain the desired attitude and position tracking control. This is done by employing a two-loop control structure. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme in the presence of disturbance, parameter uncertainty, and noise. The numerical results are compared with current approaches, demonstrating the superiority of the proposed method. In order to assess the practical effectiveness of the proposed method, hardware-in-loop simulations are conducted by utilizing a Pixhawk 6X flight controller that interfaces with the mission planner software. Finally, experiments are conducted on a real F450 quadrotor in a secured laboratory environment, demonstrating stability and good tracking performance of the proposed MLNN observer-based SMC control scheme.

Coordinated Control of Differential Drive-Assist Steering and Direct Yaw Moment Control for Distributed-Drive Electric Vehicles

Direct yaw moment control (DYC) and differential drive-assist steering (DDAS) for distributed-drive vehicles are both realized by allocating the in-wheel motor torque. To address the interference caused by overlapping control objectives, this paper proposes a multilayer control strategy that integrates DYC and DDAS, consisting of an upper controller, a coordinated decision layer, and a torque distribution layer. The upper controller, designed based on the vehicle’s dynamic characteristics, incorporates an adaptive fuzzy control DYC system and a dual PID control DDAS system. The coordinated decision layer is developed utilizing a phase-plane dynamic weighting method, delineating region boundaries by applying the double-line and limit cycle methods. The torque distribution strategy is formulated considering motor peak torque and road adhesion conditions. Multi-condition joint simulation experiments indicate that the proposed multilayer control strategy, integrating the advantages of DYC and DDAS, reduces peak steering wheel torque by approximately 10%, peak yaw rate by around 25%, peak sideslip angle by roughly 29%, and peak sideslip angle rate by about 19%, significantly improving driving stability and maneuvering flexibility.

Development of multilayer composite film based on protein‐polysaccharides with the addition of onion waste extracts and their impact on the shallot quality

AbstractAt present, multilayer composite film is attractive in the production of biodegradable films due to its essential film properties. The current study mainly focused on overcoming the problems of poor water barrier and mechanical strength observed in monolayer films (SA‐CMC and G/SA‐CMC) made from gluten (G), sodium alginate (SA), and carboxymethylcellulose (CMC). The film was developed with the addition of onion waste extracts (OWEs), primarily from peel and stalk, to enhance functional properties. The multilayer composite film consists of three layers: an outer layer made of G, an inner layer made of SA, CMC, and a middle layer made of G/SA‐CMC. The developed composite film exhibited improved physical properties (thickness: 0.348–0.629 mm and moisture: 20.889%–21.403%), mechanical properties (tensile strength: 21.943–20.640 MPa), and barrier properties (WVP: 0.212–0.516 g/m.s.Pa × 10−14) compared to monolayer films (SA‐CMC and G/SA‐CMC). The addition of OWEs enhanced the multilayer film's phenolic (20.076 and 36.175 mgGAE/g) and antioxidant activity (73.850% and 42.667%). The study found that the multilayer control film had minimal changes in weight loss (9.75% ± 0.18%) and firmness (6.68 ± 0.64 N) compared to OWEs‐added films (9.93% ± 0.49–10.02% ± 0.14% and 6.61 ± 0.37 to 6.64 ± 0.18 N). However, fresh‐peeled shallot onion packed with control film exhibited higher bacterial counts (6.70 ± 0.42 CFU/g) and yeast and mold counts (5.08 ± 0.20 CFU/g) than those packed with the OWEs‐added film (6.49 ± 0.28–6.56 ± 0.27 CFU/g and 4.75 ± 0.18–4.89 ± 0.21 CFU/g), indicating that OWEs protect the onions from microbial degradation. Overall, the multilayer control film (without OWEs) showed better results for storing the fresh‐peeled shallot onion at 4°C for 21 days.Highlights Onion waste extracts have potent high antioxidant and antimicrobial properties Multilayer film's physical, mechanical, barrier, and functional properties improved Addition of onion waste extracts increased the film's antimicrobial activity Control film showed a better effect for storing fresh‐peeled shallot onion Developed film can store fresh‐peeled shallot onion for 21 days at 4°C.

Innovative IoT Smart Lock System: Enhancing Security with Fingerprint and RFID Technology

Security concerns in residential and working environments are more critical than ever, yet traditional door locks that rely on physical keys still hold significant vulnerabilities. Those key risks include loss, misplacement, or copying and may result in unauthorized access. Moving into Industry 4.0, there is great potential to integrate IoT technology to create a far more sophisticated and resilient door access system to handle such concerns. This paper analyze the design and development of a new IoT-based smart lock system enhancing security with fingerprint recognition, RFID technology, and application control via Wi-Fi as an additional to conventional lock such as kill switch and also front desk switch. In the discussed system, the ESP8266 microcontroller is used for wireless communication. Then, Virtuino IoT applications provided the function for real-time monitoring, while HiveMQ MQTT broker secured data transmissions. Therefore, the electromagnetic locking mechanism at the door was improved by using multi-layer access control. As mentioned, the methodology would provide an integration of critical hardware parts, such as NodeMCU ESP8266, Arduino Uno and electromagnetic locks, with robust software solutions in terms of secure communication and control. Once developed, the system architecture will be simulated and tested for its effectiveness in achieving better security and operational efficiency. The opted multi-layered security system can be beneficial to residential and working environment and is designed to overcome the limitations of conventional locks. Thus, enhancing the implementation of IoT-based security solutions in everyday life.

A multilayered infection control intervention on carbapenem-resistant Acinetobacter baumannii acquisition: An interrupted time series

Carbapenem-resistant Acinetobacter baumannii (CRAB) causes life-threating hospital-acquired. Due to a limited number of Intensive-Care-Unit (ICU) beds, these patients are often treated in high-dependency (HD) non-ICUs within internal-medicine wards (IMW) in Israel. We aimed to assess the effectiveness of a multilayered infection-control intervention on CRAB infection rate in IMWs, especially in its HD non-ICUs with ongoing CRAB transmission. A quasi-experimental, before-and-after, interrupted time-series study with control outcomes. We conducted a multilayered intervention over 3.5years, which included 4 phases: (1) Pre intervention; (2) Interventionintroduction: introduced enhanced environment cleaning; (3) Intervention phase 1: introduced active surveillance; (4) Intervention phase 2: introduced CRAB-positive patient cohorting, in addition to previous ongoing measures taken. CRAB was isolated from 204 patients aged 69.8y/o±15.86y, 59.8% male, 34.3% had CRAB-positive clinical samples. Mean hospital length-of-stay was 30.5days, with a 30-day postdischarge mortality rate of 55.9%. Mean CRAB clinical cases decreased from 0.89 in preintervention to 0.11 at the end of phase 2, with a change in slope and level after the intervention of P=.02 (CI: -0.204to -0.040) and P=.004 (CI: -0.013 to -0.003), respectively. This intervention, including enhanced environment cleaning, active surveillance, and patient cohorting, successfully reduced CRAB acquisition in IMWs and their HD non-ICUs.