Owing to its unique, concealment and easy customization by combining different wrist and hand gestures, high-density surface electromyogram (HD-sEMG) is recognized as a potential solution to the next generation biometric authentication, which usually adopts a wireless body sensor network (BSN) to acquire the multi-channel HD-sEMG biosignals from distributed electrode arrays. For more accurate and reliable classification, biometric authentication requires the distributed biosignals to be sampled simultaneously and be well aligned, which means that the sampling jitters among the arrays need to be tiny. To synchronize data sampling clocks of a cluster of BSN nodes for biometric authentication, this article modifies the packet-coupled oscillators protocol by using a dynamic controller (D-PkCOs). This protocol only involves one-way single packet exchange, which reduces the communication overhead significantly. For the purpose of maintaining precise sampling of these BSN nodes subject to drifting clock frequency and varying delays, the dynamic controller is designed via the $H_\infty$ robust method, and it is proved that all the BSN nodes’ sampling jitters are bounded. The experimental results demonstrate that the D-PkCOs protocol can keep the sampling jitters less than a microsecond in a 10-node IEEE 802.15.4 network. The application of D-PkCOs to the BSN shows that the HD-sEMG signal with a high signal-to-noise ratio is obtained, which leads to better gesture classification performance.

Precise timing among wireless sensor nodes is a key enabling technology for time-sensitive industrial Wireless Sensor Networks (WSNs). However, the accuracy of timing is degraded by manufacturing tolerance, ageing of crystal oscillators, and communication delays. This paper develops a framework of Packet-Coupled Oscillator (PkCOs) to characterise the dynamics of communication and time synchronisation of clocks in WSNs. A non-identical clock is derived to describe the embedded clock's behaviour accurately. The Proportional-Integral (PI) packet coupling scheme is proposed for synchronising networked embedded clocks, meanwhile, scheduling wireless Sync packets to different slots for transmission. It also possesses the feature of automatically eliminating the effects of unknown processing delay, which further improves synchronisation performance. The rigorous theoretical analysis of PI-based PkCOs is presented via studying a closed-loop time synchronisation system. The performance of PI-based PkCOs is evaluated on a hardware testbed of IEEE 802.15.4 WSN. The experimental results show that the precision of the proportional-integral PkCOs protocol is as high as 60us (i.e., 2 ticks) for 32.768kHz crystal oscillator-based clocks.

Precise timing over timestamped packet exchange communication is an enabling technology in the mission-critical industrial Internet of Things, particularly when satellite-based timing is unavailable. The main challenge is to ensure timing accuracy when the clock synchronisation system is subject to disturbances caused by the drifting frequency, time-varying delay, jitter, and timestamping uncertainty. In this work, a Robust Packet-Coupled Oscillators (R-PkCOs) protocol is proposed to reduce the effects of perturbations manifested in the drifting clock, timestamping uncertainty and delays. First, in the spanning tree clock topology, time synchronisation between an arbitrary pair of clocks is modelled as a state-space model, where clock states are coupled with each other by one-way timestamped packet exchange (referred to as packet coupling), and the impacts of both drifting frequency and delays are modelled as disturbances. A static output controller is adopted to adjust the drifting clock. The H∞ robust control design solution is proposed to guarantee that the ratio between the modulus of synchronisation precision and the magnitude of the disturbances is always less than a given value. Therefore, the proposed time synchronisation protocol is robust against the disturbances, which means that the impacts of drifting frequency and delays on the synchronisation accuracy are limited. The one-hour experimental results demonstrate that the proposed R-PkCOs protocol can realise time synchronisation with the precision of six microseconds in a 21-node IEEE 802.15.4 network. This work has widespread impacts in the process automation of automotive, mining, oil and gas industries.

Heterogeneous Multi-Agents System (MAS) has been attracting increasing attention in many application areas, but the safety and reliability of MAS are still challenging issues. Fault diagnosis is a necessary technology to ensure the safety and reliability of heterogeneous MAS. According to the characteristics of high dispersion in MAS, strong local perception ability and weak global perception ability, this paper proposes a distributed hybrid knowledge-based and data-driven fault diagnosis, which realizes dynamic re-construction of data and knowledge through reinforcement learning and fuzzy broad learning. In the meantime, we also consider communication network topology to realize distributed collaborative diagnosis, which can effectively improve the diagnostic performance. Then, we develop a high-fidelity heterogeneous MAS software-in-the-loop and hardware-in-the-loop fault simulators to simulate different types of failures (i.e., actuator failure, sensor and communication failure). Finally, through the cross-validation on the above developed simulators, this work verifies the effectiveness of the proposed distributed intelligent fault diagnosis.

Time-sensitive wireless applications have strict requirements on real-time data transmission and control operation. Even though time synchronisation has been extensively studied for providing a common timing among distributed wireless nodes, there still exists a lack of research for low-accuracy and large-drifting clocks, such as internal Resistor-Capacitor (RC) oscillator clocks with around 4 × 10 ⁵ parts per million (ppm), which are widely used in wearable sensor systems. This paper proposes a Proportional Packet-Coupled Oscillators (P-PkCOs) protocol for synchronising poor-performing internal RC oscillator clocks with high disturbances in the single-cluster wireless network. The behaviour of such a drifting clock is described as a non-identical and time-varying model. To achieve time synchronisation on low-accuracy internal RC oscillator clocks, a packet-coupled synchronisation scheme is proposed for adjusting drifting clocks via the proportional control-based correction scheme. The RC oscillator frequency in an embedded system cannot be corrected, and this work utilises the clock threshold adjustment as a substitute for frequency correction. The stability region of controller parameters is given to guarantee that the clock threshold approaches a value, which is jointly determined by the nominal threshold and the corresponding clock frequency. We also propose a linear matrix inequality condition to prove that the P-PkCOs performance is robust against the large clock disturbances. We demonstrate the implementation of P-PkCOs. The experimental results show that P-PkCOs can achieve and maintain robust time synchronisation on the internal RC oscillator clocks.

Unmanned Aerial Swarms are attracting widespread interest in fields such as disaster response, environmental monitoring, and agriculture. However, there is still a lack of effective recovery strategies and comprehensive performance metrics for UAV swarms facing communication attacks, especially in capturing dynamic recovery. The aim of this study is to recover the split and disconnected UAV swarm under attacks. A dynamic recovery method is proposed under attacks by establishing the relationship between algebraic connectivity and consensus speed. The proposed recovery method enables each UAV to selectively establish communication links with responsive UAVs based on the proposed recovery method to reduce communication cost, rather than linking with all neighbours within communication range. Based on this, a set of performance indexes is introduced, considering factors such as consensus ability, communication efficiency, mission execution, and resource consumption. Furthermore, a resilience metric is proposed to quantitatively assess the efficiency of recovery and consensus transition, providing a comprehensive measure of the ability to reach consensus after attacks. Simulations utilizing the second-order consensus protocol and dynamics validate that the consensus speed of the proposed recovery method is $18.88\%$ faster than random recovery. The proposed resilience metric captures the change in the time from recovery to new consensus state, and the resilience of the proposed recovery method is $66.99\%$ higher than random recovery.