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A vehicle platoon is a group of vehicles driving together with a harmonized speed and a short inter-vehicle gap by using vehicle automation and vehicle-to-vehicle communication. Platoons have to share road with human-driven vehicles (HDVs) and can only be applied in heterogeneous traffic flow for a long period. Driver cut-in behavior (DCB) towards a platoon can be frequently expected in such driving context. In this paper, to understand and simulate such behavior, we propose a platoon-oriented cut-in behavior (POCB) model by fusing a lateral and a longitudinal control model into the queuing network (QN) cognitive architecture. Platoon-oriented cut-in experiments are conducted to collect driver data under cut-in from back and front scenarios, which both include six sub-scenarios with different platoon gaps or initial velocities. We demonstrate the effectiveness of the proposed model in simulating the DCB towards platoons by comparing experimental and simulation results under various driving scenarios across different subjects. Agency for Science, Technology and Research (A*STAR) Submitted/Accepted version This work was supported by the A∗STAR under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund C Pre-Positioning (IAF-PP) (Award A19D6a0053).

The distributed observer problem is motivated by the case where the output information of the system is decentralized in different subsystems. In this scene, all the subsystems form an observer network, and each of them has access to only a part of output information and the information exchanged via the given communication networks. Due to the limitation of communication conditions among subsystems, the communication network is often time varying and disconnected. However, the existing research about the aforementioned scene is still not enough to solve this problem. To this end, this article is concerned with the challenge of the distributed observer design for linear systems under time-variant disconnected communication networks. The design method is successfully established by fixing both completely decentralized output information and incompletely decentralized output information into account. Our work overcomes the limitation of the existing results that the distributed observer can only reconstruct the full states of the underlying systems by means of fast switching. In the case of completely decentralized output information, a group of sufficient conditions is put forward for the system matrix, and it is proved that the asymptotical omniscience of the distributed observer could be achieved as long as anyone of the developed conditions is satisfied. Furthermore, unlike similar problems in multiagent systems, the systems that can meet the proposed conditions are not only stable and marginally stable systems but also some unstable systems. As for the case where the output information is not completely decentralized, the results show with the observable decomposition and states reorganization technology that the distributed observer could achieve omniscience asymptotically without any constraints on the system matrix. The validity of the proposed design method is emphasized in two numerical simulations.

As the largest irrigation area in northwest China, the middle and lower reaches of the Yarkant River basin are limited in economic development by the shortage of surface water resources and the increasing demand for groundwater resources from agriculture and industry, and the phenomenon of over-exploitation is becoming increasingly serious, which is not in line with the concept of sustainable development. Therefore, improving the efficiency of water resource utilization while curbing the trend of declining groundwater levels is an important issue that needs to be addressed in the middle and lower reaches of Yarkant at present, specifically, by establishing a distributed hydrological model MIKE SHE based on a soil texture dataset. The model efficiency coefficient Ens, the water balance coefficient (WB), the correlation coefficient r, and the relative error Re were selected to evaluate the model’s applicability. The results were: Ens = 0.84, WB = 0.80, and r = 0.96 for the annual scale runoff simulation and Ens = 0.85, RE = 0.61, and r = 0.96 for the monthly scale runoff simulation. The relative errors between the simulated and observed values of the typical observation wells were 3.45%, 1.59%, 2.52%, and 0.35%. According to the analysis of the soil parameters on the runoff sensitivity and groundwater table sensitivity, the saturated hydraulic conductivity had the greatest effect on the peak discharge. The results show that the MIKE SHE model has some applicability in the lower and middle reaches of the Yarkant River basin.

Sardina pilchardus is a valuable source of bioactive peptides with potential applications in functional foods. In this study, we investigated the angiotensin-converting enzyme (ACE) inhibitory activity of Sardina pilchardus protein hydrolysate (SPH) produced using dispase and alkaline protease. Our results showed that the low molecular mass fractions (

This article addresses the cooperative fault-tolerant control problem for networks of stochastic nonlinear systems with actuator faults and input saturation. The fuzzy neural networks (FNNs) are employed to estimate the unknown functions and stochastic disturbance terms. To analyze the nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is constructed to estimate the saturation function. A novel adaptive fault-tolerant control protocol is proposed by using backstepping design technique. By using the stochastic Lyapunov functional strategy, it is proved that all the followers’ outputs eventually converge to a small neighborhood of the leader’s output, and all the signals in the closed-loop systems are bounded in probability. Finally, the performance of the proposed control strategy is illustrated through simulation.

This article develops a robust packetized predictive control framework to deal with the quantized-feedback control problem of networked systems subject to Markovian packet dropouts and input saturation. In the proposed framework, the Markov chain model of packet dropout is established from the link of the controller to the actuator. To deal with the quantized measurements, a robust packetized predictive control method is presented with a quantized-feedback law. The problem of unreliable transmission is addressed by proposing a packet dropout compensation strategy with a forgetting factor. An augmented Markovian jump system model is established to take the packet dropouts into account. The synthesis of packetized predictive control is then developed by minimizing a worst case cost function with respect to the model uncertainties. The recursive feasibility of the proposed controller design problem and the mean-square stability of the closed-loop systems are proved, respectively. The proposed packetized predictive control method is demonstrated by simulating a four-tank process system.

This article investigates the fully cooperative consensus problem for heterogeneous nonlinear multiagent systems with a leader of bounded unknown input. In the proposed framework, a novel distributed cooperative consensus algorithm is developed to derive the perfect consensus behaviors, in which the general assumption in existing works that the leader agent must have a direct link to every follower can be removed. With the formulation of some mild assumptions, the sufficient conditions for controller design are proposed to develop a class of integrated consensus protocol, which can friendly synthesize the limited interaction, compensation dynamics of the equilibrant point of the systems, appropriate feedback gains, and distributed estimation of the unknown inputs of the leader. The effectiveness of the proposed approaches are verified by simulations with multiple heterogeneous single-link manipulators.

Efficient task assignments can significantly improve agent management and reduce communication load and energy consumption. This article investigates the cooperative control problem for multiagent systems with an active task assignment strategy, in which whether an agent exchanges the information with neighbors depends on a perceived mission. By defining a set of missions, a task assignment mechanism for cooperative control problem is first proposed, in which the tasks will be scheduled by intermittent communication signals associated with the actual optimization requirements. By allowing appropriate task assignment conditions, a class of tracking cooperative control protocol is designed and accordingly, the stability of the closed-loop systems under the intermittent communication will be guaranteed. We also consider a case that the communication links between the followers and the leader can be optimized. To maximize the quality of information interaction, a leadership competition mechanism is introduced to design the tracking cooperative control protocol. As an application, cooperative surveillance using a group of rotary-wing air vehicles is considered. Numerical simulation demonstrates the effectiveness of the proposed approaches.

Abstract The dynamic wellbore pressure induced by the frictional pressure loss and swab/surge pressure may lead to wellbore instability in the process of drilling. However, the traditional wellbore stability analysis assumes a steady wellbore pressure, rather than a dynamic wellbore pressure. Therefore, to investigate the influence of dynamic wellbore pressure on wellbore stability, an elastoplastic model was proposed by involving the dynamic wellbore pressure, and the finite element method was employed to solve this model. The normalized yield zone area (NYZA) was utilized to characterize the stability of wellbore. The influences of waveform, mean pressure, amplitude, period, and cycle number of the dynamic wellbore pressure wave on wellbore stability were simulated and discussed. The results indicated that the equivalent plastic strain and NYZA increased significantly when the dynamic wellbore pressure is applied, so that the dynamic wellbore pressure has a significant impact on the wellbore stability. Both waveform and wave period almost have no impact on wellbore stability, while the mean pressure, wave amplitude, and cycle number have a significant impact on wellbore stability. Overall, the rank of influence degree on wellbore stability are as follows: cycle number > wave amplitude > mean pressure > waveform > wave period. The primary cause of wellbore instability is the accumulation of plastic damage induced by shear or compressive stress around the wellbore. Introduction Wellbore instability is a classic rock mechanics problem, it is generally caused by excessive stress concentration that exceeds rock strength. Wellbore instability costs drilling industry certainly more than $100 million per year worldwide (Fjar et al., 2008; Ma et al. 2018a; Aadnoy and Looyeh, 2019; Yang and Liu 2021).