Control Signal Transmission Research Articles

Optimizing Cable Wrapping Patterns to Neutralize Dynamic Impacts on Host Plate Structures for Space Applications

Abstract In the realm of lightweight space structures, the interplay between power and control signal transmission cables and their host structures introduces intriguing dynamics. The presented paper aims to investigate optimal geometries for cable placement on plate structures while preserving the dynamic characteristics of the host structure. The cable wrapping is assumed to be periodic such that the cable-harnessed structure consists of several repeating fundamental elements. The periodicity condition allows for the application of an energy-equivalence homogenization approach to develop an analytical model resulting in partial differential equations for the vibrations of the cable-harnessed plate system. An optimization algorithm is developed to rank various cable patterns for several host plate structures to obtain the best match for their frequency response functions compared to the bare plate when no cables are attached. Subsequently, a detailed analysis to investigate the impacts of several wrapping parameters on the system’s dynamics is carried out. Lastly, the frequency response functions for the optimal pattern from the analytical solution is validated against those from the finite element model and have shown to be in excellent agreement.

Development of Deterministic Communication for In-Vehicle Networks Based on Software-Defined Time-Sensitive Networking

To support more advanced functionality in vehicles, there is the challenge of deterministic and reliable transmission of sensor data and control signals. Time-sensitive networking (TSN) is the most promising candidate to meet this demand by leveraging IEEE 802.1 ethernet standards, which include time synchronization, traffic shaping, and low-latency forwarding mechanisms. To explore the implementation of TSN for in-vehicle networks (IVN), this paper proposes a robust integer linear programming (ILP)-based scheduling model for time-sensitive data streams to mitigate the vulnerabilities of the time-aware shaper (TAS) mechanism in practice. Furthermore, we integrate this scheduling model into a software-defined time-sensitive networking (SD-TSN) architecture to automate the scheduling computations and configurations in the design phase. This SD-TSN architecture can offer a flexible and programmable approach to network management, enabling precise control over timing constraints and quality-of-service (QoS) parameters for time-sensitive traffic. Firstly, data transmission requirements are gathered by the centralized user configuration (CUC) module to acquire traffic information. Subsequently, the CNC module transfers the computed results of routing and scheduling to the YANG model for configuration delivery. Finally, automotive TSN switches can complete local configuration by parsing the received configuration messages. Through an experimental validation based on a physical platform, this study demonstrates the effectiveness of the scheduling algorithm and SD-TSN architecture in enhancing deterministic communication for in-vehicle networks.

Approximation-based adaptive two-bit-triggered bipartite tracking control for nonlinear networked MASs subject to periodic disturbances

PurposeThis paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances. It considers both cooperative and competitive relationships among agents within the MASs.Design/methodology/approachIn response to the inherent limitations of practical systems regarding transmission resources, this paper introduces a novel approach. It addresses both control signal transmission and triggering conditions, presenting a two-bit-triggered control method aimed at conserving system transmission resources. Additionally, a command filter is incorporated to address the problem of complexity explosion. Furthermore, to model the uncertain nonlinear dynamics affected by time-varying periodic disturbances, this paper combines Fourier series expansion and radial basis function neural networks. Finally, the effectiveness of the proposed methodology is demonstrated through simulation results.FindingsBased on neural networks and command filter control method, an adaptive two-bit-triggered bipartite control strategy for nonlinear networked MASs is proposed.Originality/valueThe proposed control strategy effectively addresses the challenges of limited transmission resources, nonlinear dynamics and periodic disturbances in networked MASs. It guarantees the boundedness of all signals within the closed-loop system while also ensuring effective bipartite tracking performance.

Development of a full ocean depth hydraulic manipulator with heavy-duty capacity

The underwater manipulator is a versatile tool commonly used for various underwater operations. In this study, we developed a heavy-duty hydraulic manipulator capable of operating at full ocean depth. The overall system design integrates both the mechanical structure and the electric control system. The master arm controls the slave arm by transmitting control signals to the controller and valve box. The structural design of the elbow and wrist joints has been optimized to enhance the manipulator's underwater performance and operational range. Laboratory tests demonstrated the manipulator’s excellent response consistency and tracking capability across a wide range of motion. During sea trials in the Mariana Trench, the manned submersible Fendouzhe successfully deployed the manipulator, showcasing its exceptional ability to complete complex tasks.

Network control based load frequency control considering the transmission delay

AbstractThis study introduces a network‐based controller to regulate frequency within power systems. The primary objective of this investigation is to ensure the stability of power systems experiencing delays in control signal transmission. Initially, a modified networked predictor is proposed to anticipate future signals within a decentralized load frequency control framework. Subsequently, a timestamp technique is employed to actively compensate for the impact of transmission delays. Additionally, an event trigger mechanism is incorporated to complement the extended state observer and optimize signal transmission resource usage. The outcomes of the study indicate that the proposed method effectively mitigates delay effects while maintaining superior performance. Moreover, the proposed method remarkably reduces the required transmission resources.

Алгоритмы передачи информации в системах управления биологическими объектами

One of the problems of the theory of management of objects with a high degree of uncertainty of behavior is solved: the development of theoretical foundations of analysis, modeling methods and improvement of bio cybernetic systems, their algorithmic and software necessary to improve the efficiency of the management process is proposed. To solve this problem, it is proposed to use the mathematical apparatus of information theory, on the basis of which the information characteristics of the control signal transmission channel from the source to the control object through the external environment are calculated, taking into account the noise of the ecosystem of the control object. The existing systems using monomodal control signals that do not carry a semantic load are analyzed, and the disadvantages and limited possibilities of improving the control systems under consideration are described. Using the example of one of the insect behavior control systems with a trichromic view, a comparison of the results obtained using various technical means used as control signal sources was performed. For improving the efficiency of control systems, which use a multimodal control signal structure, proposed various algorithms for constructing control systems using a multimodal control signal structure are considered, namely: serial and parallel circuits, combined, combining serial and parallel algorithms for using control signal sources. As a method for further improving the efficiency of control systems for biological objects with a high degree of uncertainty, it is proposed to use biological signals containing a large semantic load for the control object, which determines its behavioral response. The directions of further research are formulated in order to maximize the amount of information transmitted to the control object.

Command filter-based adaptive neural two-bit-triggered containment control for saturated nonlinear multi-agent systems

Abstract This paper considers the adaptive two-bit-triggered containment control problem for nonlinear multi-agent systems in the presence of input saturation. Since input saturation occurs frequently in practical systems, which can affect the stability of the multi-agent systems under consideration, an auxiliary design system is introduced to address this issue. Meanwhile, considering limited transmission resources in practical systems, this paper mainly focuses on the triggering condition and the control signal transmission bits, presenting a two-bit-triggered control approach to optimize the utilization of transmission resources. Furthermore, a command filter is introduced into the design process to solve the problem of complexity explosion. The proposed method ensures that all signals of the closed-loop system are bounded and the output signals of all followers converge to a convex hull spanned by the outputs of the leaders. Finally, two simulation examples are provided to verify the validity of the presented control scheme.

Asynchronous deep reinforcement learning with gradient sharing for State of Charge balancing of multiple batteries in cyber–physical electric vehicles

This work targets the State of Charge (SoC) imbalance issue due to the mismatch across multiple batteries in cyber–physical electric vehicles (EVs) arisen from a variety of practical factors such as manufacturing tolerance, nonuniform aging process and uneven operation temperature. While most of existing SoC balancing approaches are model-based and require accurate prior knowledge, a data-driven asynchronous deep reinforcement learning (DRL) with gradient sharing is proposed to equilibrate the SoC of multiple battery packs in cyber–physical EVs under time-varying operating conditions, and the transmission of control signals in the EVs is formulated by ISO/IEC 15118 standards to ensure the security of the cyber–physical EVs. The gradient sharing (GS) based exploration scheme can expand the exploration space to diversify the actor policies in the training process and in turn reduce the entropy loss value and guarantee the convergence to the optimal policy in the long term. The proposed asynchronous advantage actor-critic with gradient sharing (A3C-GS) based SoC balancing approach trains the agents based on the output data of the multiple bidirectional DC–DC converter buck-boost circuit to avoid the use of vehicle dynamics and cumbersome operating modes that are difficult to accurately model. Furthermore, the DC bus voltage regulation is integrated simultaneously with the SoC balancing scheme. Comparison results based on simulating three/six batteries based EV system show that the proposed A3C-GS based SoC balancing scheme can achieve the highest steady-state rewards while the oscillation in the early training stage is larger resulted from a larger exploration range.

Fault tolerant micro-programmed control unit for SEU and MBU mitigation in space based digital systems

The Micro-Programmed Control Unit (MPCU) offers an alternative to conventional hardwired control circuits by employing a control store for transmitting control signals through stored control bits. Traditionally, Hamming codes are used for Single-Event Upset (SEU) protection in memory components. However, these Error Control Codes (ECC) encounter challenges, such as inconsistent code rates and limited adaptability for Multiple Bit Upsets (MBU). To address MBU protection, ECC codes with soft decoding logic are commonly utilized, leading to increased hardware complexity. This paper introduces a lightweight encoding and hard-decoding logic capable of detecting and correcting up to n2∗ upsets, achieving a code rate of ≈ 0.37. Through evaluations against both traditional and recent ECC methods, the proposed approach demonstrates enhanced fault correction capabilities compared to Hamming codes. Furthermore, it maintains a consistent code rate, incurs lower area overhead, and exhibits less hardware complexity than MBU codes by employing hard decoding logic. The suggested methodology effectively mitigates both MBU and SEUs in control stores, providing reduced delay and making it well-suited for ensuring reliability in high-speed memory applications like MPCUs.

Research of microprocessor device and software for remote control of a robotic system

The modern stage of the development of intelligent robotic systems is characterized by the expansion of fields of application, which is due to autonomous work and decision-making in conditions of uncertainty. The object of research is the system of remote control of robotic systems. During the remote control of robotic systems, problems arise that are associated with the use of wireless communication in real time. The article analyzes software and hardware implementations of various remote control systems suitable for use as part of autonomous robotic systems and analyzes promising microcontroller platforms for implementing a remote control device for a robotic system. A brief review of existing protocols for transmitting control signals using radio communication equipment and microprocessor platforms for the development of embedded systems is performed, among which a solution is selected for research. Several approaches to the control of a robotic system are highlighted – control using a wired connection and corresponding protocols, control via wireless communication or via the Internet, control via general-purpose network protocols. The target platform is chosen and justified, and the S.BUS protocol is analyzed with the provision of an algorithm for obtaining the values of the control channels from the S.BUS package. The structure and algorithm of functioning of the microprocessor remote control system based on the ESP32 microcontroller and the FreeRTOS OS are given. A study of the operation process of the proposed remote control system is carried out, for which it is placed on the chassis of a ground autonomous robotic system with four-wheel drive, and the delay time of the control signal from the receiver to the engine control modules is determined. According to the conducted analysis, the expediency of using specialized radio communication equipment with the S.BUS protocol for controlling executive devices as part of a robotic system, for precise movement control in real time, is shown.

Optical transmission of microwave control signal towards large-scale superconducting quantum computing.

With the rapid development of superconducting quantum computing and the implementation of surface code, large-scale quantum computing is emerging as an urgent demand. In a superconducting computing system, the qubit is maintained in a cryogenic environment to avoid thermal excitation. Thus, the transmission of control signals, which are generated at room temperature, is needed. Typically, the transmission of these signals to the qubit relies on a coaxial cable wiring approach. However, in a large-scale computing system with hundreds or even thousands of qubits, the coaxial cables will pose great space and heat load to the dilution refrigerator. Here, to tackle this problem, we propose and demonstrate a direct-modulation-based optical transmission line. In our experiment, the average single-qubit XEB error and control error are measured as 0.139% and 0.014% separately, demonstrating the feasibility of the optical wiring approach and paving the way for large-scale superconducting quantum computing.

Integrated Stabilizing Control for Sampled-Data NCSs With Intermittent Observation and Multiple Random Transmission Delays

In this paper, we study sampled-data networked control systems (NCSs) that operate over communication networks with multi-path channels. Due to limited bandwidth power, the delivery of observed state signals from the sensor to the controller may suffer packet loss possibility, which leads to intermittent observation. An unreliable multi-path routing network is responsible for the transmission of control signals from the controller to the actuator, subject to random transmission delays. These communication problems lead to degradation in system performance, which may even cause instability. By utilizing an idle-time-based scheduling policy with a pre-defined deadline constraint on the actuator side, we transform the affiliated integrated system into a stochastic model with constant input delay. For such implementation, we propose a set of Riccati-type stabilization conditions, which are necessary and sufficient. It is remarkable that the stabilizing control policy is designed based on the feedback of the optimal estimate with minimum mean square error. Moreover, for the scalar system, we study the uniqueness and existence property of the maximum sampling period, and derive its close form representation in terms of system parameters, service capability and packet dropout rate.

Interference Avoidance through Periodic UAV Scheduling in RIS-Aided UAV Cluster Communications

This article investigates the transmission of downlink control signals for multiple unmanned aerial vehicle (UAV) clusters in collaborative search and rescue operations in mountainous environments. In this scenario, a reconfigurable intelligent surface (RIS) mounted on the UAV is utilized to overcome obstacles between the ground base station (BS) and UAVs. By leveraging the fixed channel of the RIS to the BS, the line-of-sight (LoS) path characteristics of the air-to-air channel, and the position information of the UAV, the RIS forms a directional beam by adjusting the RIS coefficient, which points towards UAVs in the cluster. To ensure low delay in control signaling and UAV state transmission, we adopt semi-persistent scheduling (SPS), which allocates pre-specified periodic intervals to each UAV for the formation of corresponding RIS coefficients. The allocation of time slots is constrained by the transmission intervals required by different UAVs and the number of RISs available. We propose a time slot scheduling scheme for UAVs to reduce inter-cluster interference caused by RIS beams. The time slot allocation problem is formulated as a combinatorial optimization problem. To solve this problem, we first propose an intuitive greedy scheme called local interference minimization (LIM). Building upon the LIM scheme, we propose a rollout-based algorithm called rollout interference minimization (RIM). Through simulation, we compare the LIM and RIM schemes with the benchmark scheduling scheme. The results demonstrate that our proposed scheme significantly reduces interference between UAV clusters while satisfying the conditions of periodic transmission and RIS quantity constraints.

Time delay effect reduction on the wireless networked control system using an optimized FOPI-FOPD controller

Wireless Networked Control System (WNCS) is made up of an actuator, sensor, and controller that communicates through a wireless network rather than typical point-to-point cable connections. Lower maintenance costs, greater flexibility, and increased safety are the main WNCS advantages, so as a result, it has attracted a lot of researchers. Nevertheless, time delays and packet losses in wireless data transmission are classified as complicated problems, which impair WNCS output accuracy and may influence the overall system stability. Integer-Order PI-PD (PI-PD) and Fractional-Order PI-PD (FOPI-FOPD) controllers are proposed to reduce the impact of the control signal transmission's time delay and improve system performance. Matlab Simulink and True-time simulator are used to simulate the WNCS, and ZigBee protocol is used in transceiving the control signal between the controller and the system. Rotary Inverted Pendulum (RIP) acted as the controller's objective. The Grey Wolf Optimization (GWO) technique is utilized to evaluate the best controller parameters. Xbee S2 modules are used to implement the signal transmission process over ZigBee protocol. The FOPI-FOPD controller outperforms the PI-PD controller in the simulation and experimental results in decreasing the influence of time delay on system stability

URLLC-oriented secure communication for UAV relay-assisted network

In this paper, we investigate the unmanned aerial vehicle (UAV) relay-assisted secure short packet communication. The UAV acts as a decode-and-forward relay to transmit control signals from the source to the actuators in the presence of a ground eavesdropper (EV) whose imperfect channel state information is available at the UAV. Specially, non-orthogonal multiple access is adopted in our work to achieve more connections and improve the fairness of communication and the short packets are employed for data transmission to reduce the latency. Explicitly, we maximize the minimum average secrecy throughput among all actuators by jointly optimizing the UAV trajectory, transmit power and blocklength allocation, which generates a challenging optimization problem. Therefore, we propose an iterative algorithm based on block coordinate descent method and successive convex approximation technique to handle the non-convex problem. Numerical results show that the proposed scheme has better performance compared to the benchmark schemes.

Light-Controlled Large-Scale Wirelessly Reconfigurable Microstrip Reflectarrays

In this article, the concept and design of light-controlled large-scale wirelessly reconfigurable microstrip reflectarrays are proposed. Unlike conventional electrically reconfigurable microstrip reflectarray antennas (RAs) that control the aperture phase distribution by conducting wires for transmitting control signals, the proposed method utilizes light to control the ON- and OFF-state of the integrated positive-intrinsic-negative (p-i-n) diodes wirelessly and binaurally through light-sensitive resistance of photodiodes (PDs). The concept is validated by simulation first, where a 1 bit 32 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times32$ </tex-math></inline-formula> wirelessly reconfigurable microstrip RA is designed at 10 GHz with a beam-steering range of ±60° for sidelobe levels < −10 dB, marking a record of 1024 elements with a tri-layer configuration. Experimentally, the light-control scheme is further validated by a smaller porotype of 256 elements, where a light-controlled beam steering from 30° to 45° is demonstrated. Compared with conventional wired reconfigurable microstrip RAs, the proposed method resolves the wire-routing complexity on the RA and offers a new possibility for further improving the maximum directivity, upper operating frequency, and the number of independently controllable polarizations of reconfigurable microstrip reflectarrays, paving the way for developing very-large reconfigurable intelligent surfaces (VRIS). Also, the proposed concept provides a new infrastructure for information exchange between light and microwaves.

A Novel Control Method for Active Power Sharing in Renewable-Energy-Based Micro Distribution Networks

The microgrid is an emerging trend in modern power systems. Microgrids consist of controllable power sources, storage, and loads. An elaborate control infrastructure is established to regulate and synchronize the interaction of these components. The control scheme is divided into a hierarchy of several layers, where each layer is composed of multi-agents performing their dedicated functions and arriving at a consensus of corrective values. Lateral and horizontal interaction of such multi-agents forms a comprehensive hierarchical control structure that regulates the microgrid operation to achieve a compendium of objectives, including power sharing, voltage, and frequency regulation. The success of a multi-agent-based control scheme is dependent on the health of the communication media that is used to relay measurements and control signals. Delays in the transmission of control signals result in an overall deterioration of the control performance and non-convergence. This paper proposes novel multi-agent moving average estimators to mitigate the effect of latent communication links and establishes a hierarchical control scheme incorporating these average estimators to accurately arrive at system values during communication delays. Mathematical models are established for the complete microgrid system to test the stability of the proposed method against conventional consensus-based methods. Case-wise simulation studies and lab-scale experimental verification further establish the efficacy and superiority of the proposed control scheme in comparison with other conventionally used control methods.

The cortical dynamics of context-dependent language processing

ABSTRACT A previous functional magnetic resonance imaging study (Dietrich et al. [2019]. Discourse management during speech perception: A functional magnetic resonance imaging (fMRI) study. NeuroImage, 202, 116047. ) showed a contribution by the pre-supplementary motor area (pre-SMA), the inferior frontal gyrus (IFG), and the basal ganglia (BG) in the processing of discourse structure. By applying dynamic causal modelling (DCM) to the data of this previous study, we aimed to shed further light on the functional interrelationships of these areas. Discourse coherence had been manipulated by using presupposition triggers in a test sentence that either corresponded or failed to correspond to a contextual item. We found connections from pre-SMA to IFG and from pre-SMA to BG. Additionally, participants’ ability to accommodate violations modulated the coupling from the BG to the pre-SMA. We discuss this pattern in light of the aslant tract transmitting control signals from the pre-SMA to the IFG that slow down procedural processing in case of errors. The pre-SMA itself seems to be regulated by the BG depending on whether participants accommodate a violation.

Analysis and Fault-Tolerant Control for Dual-Three-Phase PMSM Based on Virtual Healthy Model

Dual-three-phase permanent magnet synchronous machines (DTP-PMSMs) are famous for their fault-tolerant capability. However, the complex modeling, high copper loss, and torque ripple under postfault operation limit their further application. In this article, a fault-tolerant control (FTC) strategy is developed for DTP-PMSMs under the open-phase fault (OPF) with straightforward modeling and smooth output torque. The virtual healthy DTP-PMSM model, where the coordinate transformation, the modulation strategy, and the controller structure remain unchanged under OPF, is adopted in the proposed FTC scheme. And the current references are derived in sinusoidal waves with minimum copper loss. The inaccurate transmission of control signals under OPF is also focused on. Comprehensive theoretical analysis shows the relationship between the controller output voltage and the actual stator voltage should be considered in the proposed FTC strategy; otherwise, distortion in torque and current will be introduced. The voltage compensation is utilized to compensate for the voltage difference and ensure the smooth torque output. Besides, a quasi proportional resonance controller is designed to further suppress the residual torque ripple. The proposed strategy will not induce complex implementation and heavy computation burden. The simulation and experimental results prove the analysis and the effectiveness of the proposed strategy.

Spatiotemporal NF-κB dynamics encodes the position, amplitude, and duration of local immune inputs.

Infected cells communicate through secreted signaling molecules like cytokines, which carry information about pathogens. How differences in cytokine secretion affect inflammatory signaling over space and how responding cells decode information from propagating cytokines are not understood. By computationally and experimentally studying NF-κB dynamics in cocultures of signal-sending cells (macrophages) and signal-receiving cells (fibroblasts), we find that cytokine signals are transmitted by wave-like propagation of NF-κB activity and create well-defined activation zones in responding cells. NF-κB dynamics in responding cells can simultaneously encode information about cytokine dose, duration, and distance to the cytokine source. Spatially resolved transcriptional analysis reveals that responding cells transmit local cytokine information to distance-specific proinflammatory gene expression patterns, creating “gene expression zones.” Despite single-cell variability, the size and duration of the signaling zone are tightly controlled by the macrophage secretion profile. Our results highlight how macrophages tune cytokine secretion to control signal transmission distance and how inflammatory signaling interprets these signals in space and time.