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This paper considers remote state estimation in cyber-physical systems (CPSs) with multiple sensors. Each plant is modeled by a discrete-time stochastic linear system with measurements of each sensor transmitted to the corresponding remote estimator over a shared communication network when their securities are interdependent due to network induced risks. A dynamic nonzero-sum game with asymmetric information is formulated in which each sensor subject to a resource budget constraint needs to decide whether to invest in security for sending data packets, taking the behaviors of other sensors into account. To overcome the difficulty in characterizing or computing the Nash equilibria (NE), the game with asymmetric information is transformed into another game with symmetric information such that the equilibrium of the original game can be obtained by solving the equilibrium of the new game. Under certain conditions, we devise a backward induction algorithm to obtain a subclass of NE of the original game, known as common information based Markov perfect equilibria (CIBMPE). Finally, a numerical example is provided to illustrate the results obtained.

In this paper, the direct current (DC) winding induced voltage in wound-field flux-switching (WFFS) machines is qualitatively analyzed with air-gap field modulation principle. Operation principle and effective harmonics of DC winding induced voltage are modelled and deduced. It is found that only air-gap field harmonics with specific spatial orders, which numerically equals to odd times of half stator poles, can contribute to DC winding induced voltage. Harmonic order of DC winding induced voltages under open-circuit only, armature reaction only, and on-load condition, are predicted for m-phase WFFS machines with any feasible stator/rotor pole number combinations. Different armature winding configurations, including concentrated winding and distributed winding, are also analyzed and compared using the winding factor. Finite element analysis is employed to verify the prediction results. Finally, a prototype is built and tested for validation.

In this article, we investigate the synchronization problem of continuous-time linear systems with time-varying output couplings. Both bidirectional and unidirectional couplings are studied. In the former one, each pair of connected subsystems can both measure the outputs consisting of the relative information, whereas in the unidirectional case, it is not necessarily the case and a specific scenario when the output matrices have a common matrix factor is considered. The distributed synchronization protocols are designed and the convergence conditions of the resulting system are established making use of switched systems theory based on the detectability assumption and appropriate graph connectivity conditions. Finally, numerical examples are given to verify the derived results.

In this paper, we study the synchronization problem of identical oscillators interacting via matrix-weighted couplings under both undirected and directed graph topologies. In contrast to the existing mechanism which makes use of the instantaneous and the derivative information of the relative state, the sampled-data technique is utilized to tackle the case when the derivative information of the relative state is unavailable. Necessary and sufficient conditions depending on the coupling gains, the sampling period, and the spectra of the matrix-weighted Laplacian, are established for achieving synchronization of the oscillators under undirected and directed graph topologies. The constraints on the matrix weights that guarantee the desired spectral property of the Laplacian are also investigated. Finally, simulation results are given to verify our theoretical results.

To enhance the steady-state performance of the virtual-vector-based model predictive current control (VV-MPCC) for a five-phase flux-switching permanent magnet motor, an improved multi-vector-based MPCC (MV-MPCC) method with geometric solution is proposed and investigated in this article. The desired voltage is employed to preselect voltage vector candidates and provide a guidance for the geometric division of a sector. According to the link between the reference voltage and the division, the optimal voltage vectors are determined and their duty ratios are obtained by projection method. Compared to the conventional MV-MPCC method using derivative method, the proposed geometric MV-MPCC method employs the desired voltage to quickly determine the voltage vectors and the corresponding duty ratio, which not only alleviates computational burden but also favors for more intuitive implementation. Finally, the effectiveness of the proposed method is verified by experiments.

In this article, we study the formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations where the distances between neighboring agents or the distances between each agent and the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors, and the acceleration of the target. In order to solve the formation problem, a limit-cycle-based controller design is delivered. We divide the overall control objective into two subobjectives, where the first is target circling that each agent keeps its own desired distance to the static/moving target as well as rotating around or remaining static relative to the target as expected, and the second is distribution adjustment that each agent maintains the desired distance to its neighbors. Then, we propose a controller comprised of two parts, where a limit cycle oscillator named a converging part is designed to deal with the first subobjective, while a layout part is introduced to address the second subobjective. One key merit of the controller is that it can be implemented by each agent in its local frame so that only local information is utilized without knowing global information. Theoretical analysis of the convergence to the desired formation, of which the agents are required to be evenly distributed on a circle around the target, is provided for the multiagent system under the proposed controller. Numerical simulations are given to validate the effectiveness of the proposed controller for the cases of general formations, and to show that no collision between agents ever takes place throughout the system's evolution.

The roundabouts exist widely in urban road networks and reduce the number of traffic crashes by reducing vehicle conflicts. However, road restrictions at the entrances and exits increase the collision possibility between vehicles as they enter or leave the roundabouts. Focusing on the driving scenes in a roundabout, this article proposes a multivehicle coordinated lane change strategy for the mandatory lane change of vehicles. First, depending on the fluctuation of the vehicle acceleration, the driver’s aggressive coefficient is defined. Second, according to the vehicle’s driving state and its distance to the exit, a cost function is proposed and model predictive control is used to control the vehicle’s motion. Moreover, the Stackelberg game is utilized to model the relationship between the lane change vehicle and its surrounding vehicles, and then to determine the timing of the changing lane. Finally, the simulation experiments verify whether the algorithm can improve the average speed of the vehicle and maintain the driving stability.

This paper focuses on the motion control problem for a quadrotor with a slung load (QSL). A dynamic model of a QSL is proposed by Lagrangian approach. We considered the air resistance of the load in the model building. Based on such a dynamical model, we propose a novel nonlinear three-loop cascade controller to realize velocity control for the load of a QSL, and the exponential stability of the whole system is proved. Numerical simulations implemented in a Matlab/SimMechanics environment demonstrate the effectiveness of the designed controller and the proposed model.

This paper studies the reach control problem for a coupled affine multi-agent system, which aims to find an affine feedback control for the trajectories of the agents to reach and exit a particular facet of a given simplex in the state space in finite time. The interactions between agents characterized by diffusive coupling prevent the effective construction of controller using the well developed techniques to study similar problems for affine single-agent systems. In fact, the affine feedback control designed for a single affine system may not work for the multi-agent case anymore as some agent can be driven to exit the simplex through a restricted facet under the influence from its coupled peers. A sufficient condition is developed to guarantee that all the agents move continuously in a cone containing the simplex and exit through the exit facets in finite time under an affine feedback control. A numerical example is given to verify the effectiveness of our derived result.

Within the set of stochastic, indecomposable, aperiodic (SIA) matrices, the class of Sarymsakov matrices is the largest known subset that is closed under matrix multiplication, and more critically whose compact subsets are all consensus sets. This paper shows that a larger subset with these two properties can be obtained by generalizing the standard definition for Sarymsakov matrices. The generalization is achieved by introducing the notion of the SIA index of a stochastic matrix, whose value is 1 for Sarymsakov matrices, and then exploring those stochastic matrices with larger SIA indices. In addition to constructing the larger set, this paper introduces another class of generalized Sarymsakov matrices, which contains matrices that are not SIA, and studies their products. Sufficient conditions are provided for an infinite product of matrices from this class, converging to a rank-one matrix. Finally, as an application of the results just described and to confirm their usefulness, a necessary and sufficient combinatorial condition, the “avoiding set condition,” for deciding whether or not a compact set of stochastic matrices is a consensus set is revisited. In addition, a necessary and sufficient combinatorial condition is established for deciding whether or not a compact set of doubly stochastic matrices is a consensus set.

This paper studies, the role of persistent flows in the convergence of infinite backward products of stochastic matrices of deterministic chains over networks with nonreciprocal interactions between agents. An arc describing the interaction strength between two agents is said to be persistent if its weight function has an infinite $l_1$ norm; convergence of the infinite backward products to a rank-one matrix of a deterministic chain of stochastic matrices is equivalent to achieving consensus at the node states. We discuss two balance conditions on the interactions between agents, which generalize the arc-balance and cut-balance conditions in the literature, respectively. The proposed conditions require that such a balance should be satisfied over each time window of a fixed length instead of at each time instant. We prove that in both cases global consensus is reached if and only if the persistent graph, which consists of all the persistent arcs, contains a directed spanning tree. The convergence rates of the system to consensus are also provided in terms of the interactions between agents having taken place. The results are obtained under a weak condition without assuming the existence of a positive lower bound of all the nonzero weights of arcs and are compared with the existing results. Illustrative examples are provided to validate the results and show the critical importance of the nontrivial lower boundedness of the self-confidence of the agents.

The work studies the stability problem of networked control systems (NCSs) exposed to various imperfections, including scheduling protocols, transmission intervals, and delays by using hybrid systems tools. First of all, the above-mentioned NCSs are converted into hybrid control systems. Then under a weaker assumption, the authors construct a novel Lyapunov function to derive a less conservative sufficient condition for the uniform global asymptotic stability of the systems. Furthermore, they derive useful upper bounds for the maximum allowable transmission interval and maximum allowable delay, which significantly improve the existing results. Finally, some examples are presented to illustrate the effectiveness of the proposed theorem.

This paper is concerned with the consensus problem of general linear dynamic multiagent systems with stochastic sampling. In this paper, the sampling intervals randomly switch between two different values. The communication topology between agents is fixed and directed. Full- and reduced-order observers are designed based on neighbor agents’ relative output information. The algorithms to construct such observers are also provided. By using the estimated states of the agents, the observer-based consensus protocol with stochastic sampling are presented. Sufficient conditions to ensure consensus in mean square are derived by using Lyapunov stability theory. Finally, simulations are given to examine the effectiveness of the proposed methods.

Based on a coupled electric circuit-magnetic field model on the basis of 2D-finite element method (FEM), the influences of modeling methods and winding types on AC calculation of a 12-slot/10-pole 54.7kW/10krpm flux-switching permanent magnet (FSPM) machine is investigated. Firstly, the influences of voltage/current-source, steady/rotating rotor between phase windings are evaluated by different modeling methods. Then, the differences of AC loss between two types of winding wires with varying frequencies are analyzed, where round and flat copper wire gauges are evaluated. Finally, an experimental modular device is built to measure AC copper loss and the measured results are consistent with the predictions.

To improve anti-disturbance performance of a five-phase flux-switching permanent magnet (FSPM) motor drive, a robust deadbeat model predictive current control (RDB-MPCC) method with disturbance observer is proposed in this paper. First, parameter sensitivity of the traditional deadbeat model predictive current control (DB-MPCC) method and the influence of parameter mismatches on system performance are theoretically analyzed. Secondly, the observer system is designed based on the simplified gain matrix. A specific and practical observer gain design scheme is proposed, which can realize accurate observation of disturbances. The proposed RDB-MPCC method can eliminate static current error caused by parameter deviations as well as improve the stability of the system. Finally, a five-phase FSPM prototype motor is used to verify the effectiveness of the proposed RDB-MPCC method.

In this paper, an asynchronous discrete-time opinion dynamics model on a social influence network is considered. At each time instant, a single individual activates and updates two state variables simultaneously. The individual’s new private opinion is a weighted average of her current private opinion, the expressed opinions of her neighbors, and a constant prejudice. Meanwhile, the individual’s new expressed opinion is equal to her current private opinion, altered due to a pressure to conform to the public opinion as perceived by the individual, being the average expressed opinion among her neighbors. We analyze the system for social networks which are rooted, and show that if no individual holds a prejudice, then a mild assumption on the activation sequence of the individuals guarantees convergence. In particular, the expressed and private opinions of all individuals converge to the same value exponentially fast, with two lower bounds on convergence speeds based on two different assumptions on the network topology. Simulations are provided to illustrate the result, and provide support to the conjecture that the system dynamics may converge even if individuals hold an existing prejudice.

A novel multitope protein-peptide vaccine against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and disease is described in this report. The initial development and characterization experiments are presented along with proof-of-concept studies for the vaccine candidate UB-612. UB-612 consists of eight components rationally designed for induction of potently neutralizing antibodies and broad T cell responses against SARS-CoV-2: the S1-RBD-sFc fusion protein, six synthetic peptides (one universal peptide and five SARS-CoV-2-derived peptides), a proprietary CpG TLR-9 agonist at low concentration as an excipient, and aluminum phosphate adjuvant. Through immunogenicity studies in Guinea pigs and rats, we optimized the design of protein/peptide immunogens and selected an adjuvant system, yielding a vaccine that provides excellent S1-RBD binding and high neutralizing antibody responses, robust cellular responses, and a Th1-oriented response at low doses. In challenge studies, UB- 612 vaccination reduced viral load and prevented development of disease in mouse and non-human primate challenge models. With a Phase 1 trial completed, a Phase 2 trial ongoing in Taiwan, and additional trials planned to support global authorizations, UB-612 is a highly promising and differentiated vaccine candidate for prevention of SARS-CoV-2 infection and COVID-19 disease.Author SummarySARS-CoV-2 virus, the causative agent of Coronavirus Disease 2019 (COVID-19), has spread globally since its origin in 2019, causing an unprecedented public health crisis that has resulted in greater than 4.7 million deaths worldwide. Many vaccines are under development to limit disease spread and reduce the number of cases, but additional candidates that promote a robust immune response are needed. Here, we describe a multitope protein-peptide vaccine platform that is unique among COVID-19 vaccines. The advantages of our approach are induction of both high levels of neutralizing antibodies as well as a Th/CTL response in the vaccinated host, which mimics the immune response that occurs after natural infection with SARS-CoV-2. We demonstrate that our vaccine is immunogenic and effective in preventing disease in several animal models, including AAV- hACE-2 transduced mice, and both rhesus and cynomolgus macaques. Importantly, no immunopathology was observed in the lungs of immunized animals, therefore showing that antibody-dependent enhancement (ADE) does not occur. Our study provides an additional, novel vaccine candidate for advancement in clinical trials to treat and prevent SARS-CoV-2 infection and COVID-19 disease.

This paper studies the evolution of an expressed and private opinion dynamics model with asynchronous updating. It is shown that under some mild connectivity and individual activation conditions, the expressed and private opinions of all individuals in the network converge to a common value exponentially fast when the susceptibility to influence of all individuals is equal to one. A numerical example verifies the theoretical result.

This paper proposes a novel control strategy to improve the stability performance for four-wheel independent drive electric vehicles in critical cornering by introducing the supervision mechanism for yaw moment control and slip ratio regulation simultaneously. The proposed control strategy is a three-level structure: the first level is composed of a yaw moment controller and a longitudinal velocity controller; the second level is made up of a tyre force distributor; and the third level consists of a slip ratio regulator. To begin with, the supervision mechanism is developed to supervise vehicle driving states and determine whether the yaw moment controller should be activated. After that, the tyre force distributor is presented to assign the resultant force/moment generated by the first level to the four independent wheels, in which average distribution, dynamic load distribution, and optimal distribution schemes are separately discussed for comparison. Also, the slip ratio regulator is designed to regulate the slip ratio within the threshold. In the end, simulations performed on a nonlinear vehicle model with eight degree of freedom validated the effectiveness of the proposed control strategy and approaches.

This paper proposes a novel Krasovskii–LaSalle theorem for discrete-time switched linear time-invariant systems. The result is utilized to guarantee exponential convergence of both leaderless and leader-following consensus of discrete-time multi-agent systems under jointly connected switching network topology. Different from the continuous-time multi-agent systems under switching networks, where the magnitude of the dwell time of switching signals is irrelevant, in the discrete-time case, this value is critical for consensus reaching. A special index, called the constrained controllability index, is defined. This index can be easily calculated and provide a tighter lower bound of the dwell time when compared to those given in the literature. With our novel method, the controllability condition on the system matrix is relaxed to the stabilizability condition, and the proposed results not only expand the existing discussions to balanced switching networks but also cover some unbalanced networks. Finally, numerical examples and simulations are provided to verify the theoretical results.