Actuator Networks Research Articles

M-estimate based diffusion active noise control algorithm over distributed networks and its performance analysis

Multi-channel active noise control (ANC) systems can achieve effective attenuation of low-frequency noise in spatial areas and have been extensively studied. Recent works have focused on the application of multitask diffusion strategies in ANC systems based on wireless acoustic sensor and actuator networks (WASAN), which show the advantages of saving computational burden and enhancing flexibility. However, these works all adopt the mean-square error minimization as the optimization criterion, which leads to severe performance degradation in the presence of impulsive noise interference. Therefore, in this paper, we exploit the M-estimate function and the augmented weight vector of the control filter to formulate a robust minimization problem and propose a distributed augmented diffusion filtered-x least mean M-estimate (DADFxLMM) algorithm for multi-channel ANC systems. The proposed algorithm leverages the M-estimate function to overcome the influence of outliers in the error signal and achieves robustness against impulsive noise, and also eliminates the dependence on the symmetry of the acoustic paths by integrating the augmented weight vectors. Moreover, we replace the score function with the update probability of the weight vector to avoid the need for integration and Price’s theorem, and analyze the mean and mean-square performance of the proposed DADFxLMM algorithm under the contaminated Gaussian (CG) noise model. Simulation results under different system configurations demonstrate that the proposed algorithm outperforms the existing multi-channel ANC algorithms in the presence of impulsive noise interference.

SHM System Architecture based on Ultrasonic Guided Waves for Aircraft Application Scenarios

Structural health monitoring (SHM) based on ultrasonic guided waves is a novel technology using permanently attached actuator and sensor networks, data acquisition and data evaluation systems to enable in-service inspection of aircraft structures. A modular and decentralized SHM system is presented that can be adapted to various aircraft application scenarios. The central element of the SHM system is a robust sensor array based on piezocomposite technology that can be efficiently integrated into the manufacturing process of CFRP structures (via co-bonding). The sensor array consists of integrated piezoceramic transducers, temperature sensors, electrical cables and integrated electronic components. The decentralized system architecture of the individual electronic components reduces the installation and cabling effort during the assembly of aircraft structures as well as the system weight. Integration and installation aspects as well as various system architectures are discussed using an Airbus A350 door surround structure. Furthermore, an outlook of damage detection under representative flight loads is given.

Adaptive Control of Constrained Nonlinear CPSs Under Deception Attacks Through Sensor and Actuator Networks

Adaptive Control of Constrained Nonlinear CPSs Under Deception Attacks Through Sensor and Actuator Networks

Performance Analysis of Object Placement Systems Based on Siemens S7-1200 its’ Evaluation of Effectiveness and Accuracy

The evolution of industrial automation systems has led to innovative solutions for efficient and precise object manipulation. This study introduces a groundbreaking "Object Placement System Based on Siemens S7-1200," designed to enhance object positioning tasks in manufacturing environments. The system's core control unit is the Siemens S7-1200 Programmable Logic Controller (PLC), seamlessly integrated with a network of sensors and actuators for coordinated operations. Operators can easily define target positions and parameters for object placement through a user-friendly human-machine interface. The PLC facilitates real-time data exchange with sensors, enabling accurate object detection and adjustments during placement. The system's implementation involves meticulous PLC programming, sensor integration, and interface design. Experimental results validate its capability to achieve precise and repeatable object placements. The Siemens S7-1200 is a versatile PLC supporting controlled positioning of electrically driven axes and technology objects, tailored for small automation systems requiring simple or advanced Human-Machine Interface (HMI and communication capabilities. The object placement system leverages the capabilities of the S7-1200 PLC for integrated sensor and actuator coordination, ensuring accuracy and repeatability. The study concludes that the innovative system utilizing the Siemens S7-1200 PLC underscores its potential for optimizing production processes and enhancing operational efficiency in industrial automation systems. The demonstrated ability to achieve precise and repeatable object placements highlights the viability of the Siemens S7-1200 platform for advancing object manipulation in industrial settings. The S7-1200 system manual provides specific information about the operation and programming of the PLC. Additionally, the system is supported by the TIA Portal programming software, which offers flexibility and ease of use.

A diffusion filtered-x affine projection algorithm for distributed active noise control

The well-known Filtered-x Affine Projection (FxAP) algorithm is usually deemed a better choice than the conventional Filtered-x Least-Mean-Square (FxLMS) algorithm when faster convergence speed is desired in active noise control applications. However, the improvement of its convergence performance is obtained at the expense of increased computational complexity. It is usually unrealistic to regulate multichannel ANC systems using the centralized AP algorithm. Recently, distributed diffusion adaptation schemes over acoustic sensor and actuator networks have been introduced to multichannel ANC systems, such as the Diffusion FxLMS algorithms. Distributed processing based on diffusion cooperation strategy allocates the computation load to the network nodes in a scalable manner. This paper proposes a distributed Diffusion Filtered-x AP (DFxAP) algorithm for multichannel ANC systems. Simulation results and computational complexity analysis show that the DFxAP algorithm outperforms the Diffusion FxLMS algorithm in convergence performance and has lower computational complexity compared to the centralized AP algorithm.

Evaluation of Regional Road Transport Safety Service Level With Edge Computing in Scalable Sensor and Actuator Networks

In contemporary society, road transport has assumed a pivotal role in the daily lives of individuals, with virtually everyone being a road user in one capacity or another. Unfortunately, a significant portion of road accidents stem from user negligence and a lack of awareness regarding road safety principles and regulations. The majority of these accidents are fundamentally a result of human errors, errors that could potentially be averted through the comprehensive utilization of technology. The integration of edge computing within actuator networks, combined with the scalability of sensors, holds the potential to proactively detect and prevent impending collisions. This cutting-edge approach not only accumulates and processes sensor-generated data but also employs it to mitigate the occurrence of road accidents. This discussion delves into the potential advantages offered by smart sensors and advanced technology, focusing on the enhancement of safety within transportation networks. The core attributes of these intelligent technologies facilitate the establishment of robust connectivity and the effective implementation of processes, ushering in an innovative era in the realm of road safety through smart technology.

Online Distributed Schedule Randomization to Mitigate Timing Attacks in Industrial Control Systems

Industrial control systems (ICSs) consist of a large number of control applications that are associated with periodic real-time flows with hard deadlines. To facilitate large-scale integration, remote control, and co-ordination, wireless sensor and actuator networks form the main communication framework in most ICSs. Among the existing wireless sensor and actuator network protocols, WirelessHART is the most suitable protocol for real-time applications in ICSs. The communications in a WirelessHART network are time-division multiple access based. To satisfy the hard deadlines of the real-time flows, the schedule in a WirelessHART network is pre-computed. The same schedule is repeated over every hyperperiod (i.e., lowest common multiple of the periods of the flows). However, a malicious attacker can exploit the repetitive behavior of the flow schedules to launch timing attacks (e.g., selective jamming attacks). To mitigate timing attacks, we propose an online distributed schedule randomization strategy that randomizes the time-slots in the schedules at each network device without violating the flow deadlines, while ensuring the closed-loop control stability. To increase the extent of randomization in the schedules further, and to reduce the energy consumption of the system, we incorporate a period adaptation strategy that adjusts the transmission periods of the flows depending on the stability of the control loops at runtime. We use Kullback-Leibler divergence and prediction probability of slots as two metrics to evaluate the performance of our proposed strategy. We compare our strategy with an offline centralized schedule randomization strategy. Experimental results show that the schedules generated by our strategy are 10% to 15% more diverse and 5% to 10% less predictable on average compared to the offline strategy when the number of base schedules and keys vary between 4 and 6 and 12 and 32, respectively, under all slot utilization (number of occupied slots in a hyperperiod). On incorporating period adaptation, the divergence in the schedules reduceat each period increase with 46% less power consumption on average.

Distributed robust‐multivariate‐observer‐based FDI attacks estimation for nonlinear multi‐agent systems with directed graphs

AbstractThis article investigates the distributed robust estimation problem for false data injection (FDI) attacks in nonlinear multi‐agent systems with directed graphs. To approximate the realistic attack scenario, the case where both the actuator network channel and sensor network channel suffering from FDIs are considered, and the attack signals contain time‐varying circumstances. A novel distributed robust‐multivariate‐observer (DRMO) strategy is developed such that the online estimation of FDI attack dynamics can be realized with the partially unknown nonlinear dynamics, attack transient increments, and disturbances impact being eliminated. The designed DRMO scheme only depends on the received compromised/uncompromised measurement output information on the account that whole state information cannot be measured directly. Finally, two simulation examples, including a network of four one‐link flexible joint manipulator systems with comparisons to existing methods, are given to show the effectiveness of the proposed scheme.

Enhancing Energy Efficiency and Fast Decision Making for Medical Sensors in Healthcare Systems: An Overview and Novel Proposal.

In the realm of the Internet of Things (IoT), a network of sensors and actuators collaborates to fulfill specific tasks. As the demand for IoT networks continues to rise, it becomes crucial to ensure the stability of this technology and adapt it for further expansion. Through an analysis of related works, including the feedback-based optimized fuzzy scheduling approach (FOFSA) algorithm, the adaptive task allocation technique (ATAT), and the osmosis load balancing algorithm (OLB), we identify their limitations in achieving optimal energy efficiency and fast decision making. To address these limitations, this research introduces a novel approach to enhance the processing time and energy efficiency of IoT networks. The proposed approach achieves this by efficiently allocating IoT data resources in the Mist layer during the early stages. We apply the approach to our proposed system known as the Mist-based fuzzy healthcare system (MFHS) that demonstrates promising potential to overcome the existing challenges and pave the way for the efficient industrial Internet of healthcare things (IIoHT) of the future.

Towards the Cognitive Factory in Industry 5.0: From Concept to Implementation

Industry 5.0 (I5.0) represents a shift towards a human-centered industry and emphasizes the integration of human and machine capabilities. A highly compatible concept for enabling the I5.0 implementation is intelligent spaces (ISs), i.e., physical spaces equipped with a network of sensors, which obtains information about the place it observes, and a network of actuators, which enables changes in the environment through computing services. These spaces can sense, interpret, recognize user behavior, adapt to preferences, and provide natural interactions between humans and intelligent systems, using the IoT, AI, computer vision, data analytics, etc., to create dynamic and adaptive environments in real time. The integration of ISs and I5.0 has paved the way for the development of cognitive factories, which transform industrial environments into ISs. In this context, this article explores the convergence of IS and I5.0 concepts and aims to provide insights into the technical implementation challenges of cognitive factories. It discusses the development and implementation of a laboratory replica of a cognitive cell as an example of a segment of a cognitive factory. By analyzing the key points and challenges associated with cognitive cell implementation, this article contributes to the knowledge base surrounding the advanced manufacturing paradigm of I5.0.

Omnidirectional compliance on cross-linked actuator coordination enables simultaneous multi-functions of soft modular robots

Earthworms have entirely soft bodies mainly composed of circular and longitudinal muscle bundles but can handle the complexity of unstructured environments with exceptional multifunctionality. Soft robots are naturally appropriate for mimicking soft animal structures thanks to their inherent compliance. Here, we explore the new possibility of using this compliance to coordinate the actuation movements of single-type soft actuators for not only high adaptability but the simultaneous multifunctionality of soft robots. A cross-linked actuator coordination mechanism is proposed and explained with a novel conceptual design of a cross-linked network, characterization of modular coordinated kinematics, and a modular control strategy for multiple functions. We model and analyze the motion patterns for these functions, including grabbing, manipulation, and locomotion. This further enables the combination of simultaneous multi-functions with this very simple actuator network structure. In this way, a soft modular robot is developed with demonstrations of a novel continuous-transportation mode, for which multiple objects could be simultaneously transported in unstructured environments with either mobile manipulation or pick-and-place operation. A comprehensive workflow is presented to elaborate the cross-linked actuator coordination concept, analytical modeling, modular control strategy, experimental validation, and multi-functional applications. Our understanding of actuator coordination inspires new soft robotic designs for wider robotic applications.

Asynchronous network firmware update over the air designed for wireless sensor and actuator networks

This paper improvies the traditional FOTA system to a more robust one named ANFUOTA. This technique is only applicable to systems without embedded operating systems and to microcontrollers without multiple flash memory bank. This novel system is capable of updating the firmware in an asynchronous mode via networks WSN/WSAN kind and furthermore, it guarantees that the system never be without a valid firmware or rather, it is immune of communication failure or loss of packets and even feeding loss, independently of the updating phase. Even during the memory rewriting, in case it happens a feeding failure, the system will begin all over again the recording in the next rebooting. The used technique foresses an updating via networks WSN kind in an asynchronous mode and the firmware can be received in a distributed way in time and in many pieces or capable of being continuous. During this phase, the system remains online and doesn't enter in recording mode, keeping its activity on network. The system guarantees immunity in face of feeding loss and loss of packets by the network in all phases of updating, enabling updating all devices in network, simultaneously.

Recent Advances in Time-Sensitive Network Configuration Management: A Literature Review

At present, many network applications are seeking to implement Time-Sensitive Network (TSN) technology, which not only furnishes communication transmission services that are deterministic, low-latency, highly dependable, and have ample bandwidth, but also enables unified configuration management, permitting different network types to function under a single management system. These characteristics enable it to be widely used in many fields such as industrial sensor and actuator networks, in-vehicle networks, data center networks, and edge computing. Nonetheless, TSN’s configuration management faces numerous difficulties and challenges related to network deployment, automated operation, and maintenance, as well as real-time and safety assurance, rendering it exceedingly intricate. In recent years, some studies have been conducted on TSN configuration management, encompassing various aspects such as system design, key technologies for configuration management, protocol enhancement, and application development. Nevertheless, there is a dearth of systematic summaries of these studies. Hence, this article aims to provide a comprehensive overview of TSN configuration management. Drawing upon more than 70 relevant publications and the pertinent standards established by the IEEE 802.1 TSN working group, we first introduce the system architecture of TSN configuration management from a macro perspective and then explore specific technical details. Additionally, we demonstrate its application scenarios through practical cases and finally highlight the challenges and future research directions. We aspire to provide a comprehensive reference for peers and new researchers interested in TSN configuration management.

Integrated Logic for Dielectric Elastomers: Replicating the Reflex of the Venus Flytrap

AbstractDielectric elastomers (DEs) are electroactive polymers commonly used in soft robotics. Bulky and stiff high‐voltage circuits are usually needed to control their operation. This article presents autonomous control in a multi‐functional device made entirely of DEs. A gripper made of DE actuators is controlled by dielectric elastomer sensors through an electrical circuit. The circuit itself is composed of a network of actuators and sensors. The final structure requires only a constant power supply to work and produces its controlling signals. Every component can be manufactured simultaneously with the same materials and processes. At first, the logical control of the gripper is demonstrated by directly connecting a sensor to the gripper that opens when the sensor is stretched. Then, a DE level‐triggered flip‐flop (also called latch) is introduced to have bi‐stability between open and closed states. Finally, the latch is integrated inside the gripper, allowing it to sense objects. The device autonomously grips an object that is placed in it, resembling the closing mechanism of the plant Dionaea muscipula, also known as the Venus flytrap.

Negotiation of the global grid inspection UAV with random delay uncertainty in an information communication network based on a robust fault tolerance mechanism

To accurately simulate the interference mechanism of information communication between unmanned aerial vehicles (UAVs) in the future global grid system, a type of control based on dynamic simulation of the satellite communication network and robust fault tolerance with a stochastic delay uncertain network system is proposed. Based on the imaginary future of the global energy Internet, with unknown information and communication interference, we established a UAV model from sensor to actuator network delay using a robust, fault-tolerant control algorithm and a satellite communication network model that combined the controller’s mathematical model. The simulation results showed improved power transmission capability and communication coverage ability of UAVs by using the network fault-tolerant control mechanism with uncertain network delay and information communication interference. The stability and anti-interference performance was also significantly improved. This algorithm provides a strategy for the future development of global energy Internet.

An Enhanced and Secure Trust-Aware Improved GSO for Encrypted Data Sharing in the Internet of Things

Wireless sensors and actuator networks (WSNs) are the physical layer implementation used for many smart applications in this decade in the form of the Internet of Things (IoT) and cyber-physical systems (CPS). Even though many research concerns in WSNs have been answered, the evolution of the WSN into an IoT network has exposed it to many new technical issues, including data security, multi-sensory multi-communication capabilities, energy utilization, and the age of information. Cluster-based data collecting in the Internet of Things has the potential to address concerns with data freshness and energy efficiency. However, it may not offer reliable network data security. This research presents an improved method for data sharing and cluster head (CH) selection using the hybrid Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method in conjunction with glowworm swarm optimization (GSO) strategies based on the energy, trust value, bandwidth, and memory to address this security-enabled, cluster-based data aggregation in the IoT. Next, we aggregate the data after the cluster has been built using a genetic algorithm (GA). After aggregation, the data are encrypted and delivered securely using the TIGSO-EDS architecture. Cuckoo search is used to analyze the data and choose the best route for sending them. The proposed model’s analysis of the results is analyzed, and its uniqueness has been demonstrated via comparison with existing models. TIGSO-EDS reduces energy consumption each round by 12.71–19.96% and increases the percentage of successfully delivered data packets from 2.50% to 5.66%.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming.

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

An Architecture for Experiments in Connected and Automated Vehicles

Rapid prototyping of CAV is challenging because of the physical distribution of vehicles. Furthermore, experiments with CAV may be subject to external influences which prevent reproducibility. This article presents an architecture for the experimental testing of CAV, focusing on decision-making. Our architecture for experiments of CAV is strictly modular and hierarchical, and therefore it supports an easy and rapid exchange of every single controller as well as of optimization libraries. Additionally, the architecture synchronizes the whole network of sensors, computation devices, and actuators. Thus, it achieves deterministic and reproducible results, even for time-variant network topologies. Using this architecture, we can include active and passive vehicles and vehicles with heterogeneous dynamics in the experiments. The architecture also allows for handling communication uncertainties, e.g., data packet drop and time delay. The resulting architecture supports performing different in-the-loop tests and experiments. We demonstrate the architecture in the CPM Lab using 20 vehicles on a 1:18 scale. The architecture can be applied to other domains.

A Review of Internet of Things (IoT) and Security Concerns

Wireless technology networks are particularly vulnerable to security attacks. Wireless communication networks are widely used in education, defense, industry, healthcare, retail, and transportation. These systems rely on wired and cellular networks. In society and industry, wireless sensor networks, actuation networks, and vehicle networks have garnered a lot of attention. The Internet of Things has gotten a lot of research attention in recent years. The Internet of Things is regarded as the internet's future. IoT will play an important role in the future, changing our lifestyles, standards, and business structures. The use of IoT in various applications is likely to skyrocket in the next years. The Internet of Things enables billions of devices, people, and services to communicate and exchange information. IoT networks are vulnerable to several security vulnerabilities as a result of the rising use of IoT devices. It is crucial to implement effective privacy and security protocols in IoT networks to guarantee, among other things, confidentiality, authentication, access control, and integrity. This paper provides a thorough analysis of the security and privacy challenges in IoT networks. Keywords: Internet of Things, Security, Security Concerns, Attacks, Networks, Internet

Smart Agriculture Solutions for Vietnamese Farmers

Agriculture is the back bone of Vietnam and more than 70% of people in Vietnam depend on agriculture. Nowadays, agriculture crops are affected due to many environmental changes. To overcome this problem, I design and prototype a wireless sensor and actuator network for smart agriculture application. The aim of this work is to be able to capture useful data to start predicting measurements and events that could help farmers and specialists to save time and money. I propose two solutions for smart agriculture. In the first solution, wireless sensor and actuator nodes monitor multiple environmental parameters and transmit the sensor data to a server via the internet. Users can monitor these environmental parameters from anywhere via the internet. In the second solution, wireless sensor and actuator nodes send data to a local computer. This computer is deployed in a technical room. The experiments show that both solutions operate well in real conditions.