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This work investigates the tracking consensus problem of multiagent systems over directed networks, where the control gains follow certain volatile patterns. Some event-based consensus protocols are formulated so as to reduce the redundant execution of control. By using an extended differential inequality with a time-dependent coefficient, criteria for tracking consensus under time- and state-dependent triggering conditions are constructed, respectively. It is proved that the time average of the control gain, together with the agent dynamics, network topology, and triggering conditions, governs the consensus despite the fluctuation of control gain. The derived theorem can be utilized to ensure consensus with intermittent strategies aiming to lessen the burden in communications, including aperiodic on-off control with periodic perturbation and pulse-modulated on-off control. Unlike existing works, the requirement of a positive lower bound of control ratios is removed and, thus, a wide range of control gain patterns is possible, signifying higher flexibility in intermittent policy design. Finally, numerical examples are provided to further illustrate the theoretical results.

A two-stage stochastic programming model is established to minimize EV's expected total journey time under stochastic traffic conditions, by jointly optimizing the allocation of chargers and the distribution of EV flows. Based on sample average approximation, a feasible deterministic equivalent of the original stochastic problem is obtained. Then, a hybrid solution method, composing of a Tabu-based search and sequential quadratic programming (SQP), is proposed. The Tabu heuristic manages the charger allocation problem, where each solution candidate undergoes a second-stage EV flow optimization. SQP is applied to optimally distribute the EV flows, which is proved to be a convex problem. Extensive simulations are carried out using the eastern Massachusetts highway network. Results show that the proposed algorithm outperforms existing approaches by finding high-quality charger allocation and optimal flow distribution policies under different traffic conditions. Additionally, the two-stage model designates charging resource sufficiency by statistically estimating a lower bound for the number of chargers to allocate, which in practice helps to prevent over-investment on charging resources.

This paper is devoted to the consensus problem of networked nonlinear agents with multiple self-delays and time-varying coupling. We first establish a generalized Halanay’s inequality based on comparison theorem, and then convert the consensus problem into a stability problem of retarded differential equation with time-varying coefficients, from which sufficient conditions for consensus are derived. Our results manifest that the time-average of coupling strength over intervals of certain length, together with the underlying topology and the values of self-delays, plays a crucial role in guaranteeing consensus. Based on the theoretical analysis, an estimation of the largest admissible delay is also available. This paper provides a general framework for achieving consensus in agents with time-varying coupling, such as coupling with external perturbations, intermittent control in on–off fashion, or pulse-modulated coupling strength, etc. Furthermore, useful criteria are given for various applications which have also been verified with numerical simulations.

In this paper, the synchronization problem for networked nonlinear agents with time-varying control gain is studied under a synchronous periodic data sampling framework. To achieve synchronization, both the state-dependent and time-dependent event-triggered protocols are proposed. The effectiveness of these protocols is justified by Lyapunov stability theorem based on rigorous mathematical proof, facilitated by a delayed differential inequality with time-dependent parameters. Instead of specifying a lower bound for the control gain, as others usually suggested, our criteria rely on its time-average and thus allow higher flexibility in controller design. Numerical simulations are also presented to confirm the reaching of synchronization and demonstrate the wide applicability of the proposed protocols.

A hierarchical quantum secret sharing scheme is proposed, for which participants are divided into multiple layers. In this scheme, the number of participants and the shared secrets can be different for layers. The shared secret of a layer can only be recovered by the cooperation of all the participants at that layer. Moreover, each participant is able to obtain the shared secrets at lower layers, but not those at higher layers. The design is based on a special high-dimensional entangled state, in which the particles have different dimensions and can be set as subtle values to satisfy the hierarchical requirement. The correctness and security of the proposed scheme are analyzed. As compared to existing quantum secret sharing schemes, it possesses distinct features which are demanded by some specified scenarios.

In recent years, the popularity of electric vehicles (EVs) has been rapidly expanding, thanks to the government’s supportive policies. However, managing EV’s en-route re-charge activities under different operation scenarios is still a critical issue, when the EV’s limited driving range and long re-charge time are concerned. In this paper, an EV flow distribution problem is formulated for the guidance of EV’s re-charge activities. The problem manipulates EV flows directly with the consideration of EV’s queuing and re-charge delay at charging stations, which makes it greatly different from the classic problems. To solve the problem effectively, a dedicated flow distribution algorithm (FDA) is devised. Furthermore, based on the centrality properties in the context of complex network science, the interdependence of EV flow distribution and charging resource allocation is investigated. Simulation results show that a proportional allocation of chargers to nodes with high weighted betweenness leads to the most efficient flow distribution. In addition, robustness is introduced to measure the flow distribution solution’s endurance under EV drivers’ ignorance of guidance. The comparison among centrality-based allocations and an optimization-based allocation reveals that efficiency and robustness are two conflicting properties in flow distribution, dependent on the allocation of charging resources.

This paper investigates the synchronization problem of nonlinear multi-agent systems with time-varying control in the presence of transmission delay over a communication network. To facilitate the study, a novel delayed differential inequality with time-varying coefficients is first established. Then, the synchronization problem is recast into the stability problem of a delayed differential system with certain time-dependent parameter. A sufficient criterion is further formulated to guarantee the synchronization. The mathematical proof reveals that the time average of the control strength is crucial for reaching synchronization. Together with the agent dynamics and the topology, this average also governs the largest admissible delay. Moreover, the criterion is applied to synchronization problems with general on-off coupling under data sampling and delayed communications, respectively. Some useful corollaries are consequently deduced. Finally, numerical simulations are presented to illustrate the validity of our theoretical results.

For the benefit of global environmental preservation, electric vehicles (EVs) have been gradually accepted by people in the past few years. However, the technical problem of limited drivable range and long charging duration is still a major hurdle for the popularization of EVs, especially for commercial usage. In this paper, a dynamic electric vehicle routing problem (D-EVRP) model is designed for planning the itinerary for goods delivery by the utilization of EVs in logistics industry. To reflect the real situation, the D-EVRP considers a time-dependent stochastic traffic condition and captures the discharging/charging pattern of an EV using an analytical battery model. Its aim is to minimize the overall service duration, subject to a variety of the state-of-art constraints common in EV routing problems. Furthermore, to address the D-EVRP, a hybrid rollout algorithm (HRA), which incorporates a dedicated pre-planning strategy and a rollout algorithm, is also proposed. The effectiveness of the HRA and benefits of incorporating the analytical battery model are justified by extensive simulations using the real-world D-EVRP instances.

This brief addresses the consensus problem of a group of agents coupled via nonlinear locally passive functions over a time-varying network. A consensus protocol is designed which is solely dependent on an agent’s own instantaneous state and the states broadcasted from its neighbors. A time-dependent triggering condition is defined to govern the broadcasting of one’s state to all its neighbors. Information exchange only occurs when the triggering condition is met, as a result, communication overhead can be greatly reduced. It is mathematically proved that consensus is reachable and Zeno behavior is excluded if the union of the underlying graphs over any time interval of certain length admits a directed spanning tree. The proposal is applicable for various kinds of networks, such as continuously time-varying network, switching network, blinking network, and its effectiveness is confirmed with numerical examples.

In this brief, a multi-carrier differential chaos shift keying system capable of mitigating channel noise is proposed. In this system, subcarriers are allocated to the reference and data signals in an optimal way, while noise reduction is achieved through reference diversity. To verify its performance, the bit error rate of the proposed system over multipath Rayleigh fading channels is derived, together with a detailed discussion about the determination of the optimal number of reference-carrying subcarriers. Extensive simulations are carried out for performance evaluation, which are further compared to other state-of-the-art systems. Results confirm the superior bit error rate performance of the proposed system, which has only small loss in energy and spectral efficiencies.

This paper proposes an event-triggered protocol to achieve consensus in multi-agent system, in which neighboring agents are coupled via a nonlinear function with local passivity. It is mathematically proved that the proposed protocol guarantees average consensus in the system, excluding the existence of Zeno phenomenon. As a practical application, the scheme is applied to achieve synchronization in the Kuramoto oscillator network. Phase agreement is obtained for oscillators with identical natural frequency. For oscillators with non-identical natural frequencies, their phases are confined in a bounded range and their frequencies reach an average of their natural frequencies. To further demonstrate the generality of the scheme, another multi-agent system with coupling based on exponential and tangent functions is also presented. All the simulation results verify the condition of consensus and confirm the effectiveness of the scheme.

Based on multi-carrier transmission and multi-level chaos shift keying modulation, a novel multi-carrier chaos shift keying (MC-CSK) modulation system is proposed and designed in this paper. The new system adopts multiple subcarriers, on which all chaotic basis signals along with multiple data-bearing signals are transmitted simultaneously. The data-bearing signals and their references, though sharing the same subcarriers, are separated by I/Q channels. As a consequence, the MC-CSK system can achieve higher bit rate and better spectral efficiency compared with the MC-DCSK system. It can also dispense with chaos synchronization and threshold shifting that are required in conventional CSK systems, and achieve a delay-line-free design in both transmitters and receivers. Also, the performance of the proposed system is further improved by normalizing all chaotic basis signals and making them strictly orthogonal using the Gram-Schmidt algorithm. Moreover, the bit error rates (BERs) of the MC-CSK system over additive white Gaussian noise and multipath Rayleigh fading channels are derived. Finally, simulations are performed under different channel conditions and the effects of system parameters on the BER performance are evaluated. Both analytical and simulation results confirm that the MC-CSK system outperforms differential CSK (DCSK) and MC-DCSK systems in BER performance, except a rare case when the number of subcarriers is very small.

A novel non-coherent multi-level differential chaos shift keying (DCSK) modulation scheme is proposed in this paper. This new scheme is based on both the transmitted-reference technique and $M$ -ary orthogonal modulation, where each data-bearing signal is chosen from a set of orthogonal chaotic wavelets constructed by a reference signal. Thanks to this signaling design, the new scheme can achieve a higher attainable data rate, lower energy loss in reference transmission, increased bandwidth efficiency, better data security and better bit error rate (BER) performance as compared to the conventional DCSK. Unlike other DCSK-based systems that separate the reference and data-bearing signals using the TDMA scheme, this new system employs I/Q channels to send these two signals in a parallel and simultaneous manner, making the system easily extendable to multi-carriers. This transmission mechanism not only can further increase data rate but also can remove all radio frequency delay lines from detectors. Analytical BER expressions of the proposed system are derived for both additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Relevant simulation results are given and compared to non-coherent binary/ $M$ -ary DCSK systems. In addition, the impacts of various system parameters on noise performance are discussed. Both theoretical analysis and simulation results confirm the promising benefits of the new design.

This work studies the consensus problem of a group of agents with nonlinear dynamics while directional communications between agents with delay are assumed. To reflect the practical situation of having reconnections or disconnections between agents, the communication topology is considered to be switched within a finite set of digraphs. The consensus criterion with exponential convergence is established by the use of linear matrix inequalities and multiple Lyapunov functional theory. It is interesting to point out that consensus is still possible even though some agents are isolated from the others intermittently. These theoretical results are also well illustrated with numerical simulations.

This work considers the leader-following problem of a network of agents with nonlinear dynamics. To reflect a more practical case, the network topology is assumed to be arbitrarily switching among a finite set of topologies and the time-varying delay exists in the coupling of agents. Based on the common Lyapunov function theory, sufficient conditions for the asymptotical stability of this multiagent system are derived, which in turns, can be managed by the linear matrix inequality method. A sufficient stability condition is derived to provide a tight condition for stability, applicable for networks with considerable sizes. On the other hand, when a multitude of agents is involved, a comparative conservative but efficient criterion is also proposed. Both criteria only demand on low dimensional matrices, which are independent of the network size. Moreover, some simple stability criteria for the cases without coupling delay are also established. A simple optimization scheme is also formulated to determine the largest allowable delay. Finally, numerical simulations are provided to illustrate the feasibility and effectiveness of the obtained theoretical results.

In this brief, a new scheme is developed for chaos control by applying periodic impulsive parametric perturbations. Based on Melnikov's condition for the existence of chaos, it is mathematically proven that, in a neighborhood of a homoclinic orbit of the Duffing system, chaos can be suppressed. A sufficient condition is also established, serving as the design criterion for the amplitude and the width of the impulsive control signal. Finally, the control effect will clearly be demonstrated with simulation results.

Recently, the identification of biological neural networks has been reformulated as an optimization problem based on a framework of adaptive synchronization. In this paper, four different optimization algorithms, including genetic algorithm, jumping gene genetic algorithm (JGGA), tabu search, and simulated annealing, have been applied for this optimization problem. Based on the simulation results, their performances are compared, and it is concluded that JGGA can outperform the other three methods in term of minimizing the synchronization and parameter estimation errors.

This paper explores the generation of n- and n times m-wing Lorenz-type attractors from a modified Shimizu-Morioka system. The basic idea is to increase the number of index-2 equilibrium points by introducing a multisegment quadratic function and a stair function in the 2-D state-space of the system. The design is verified by both simulation and experiment, where multiwing attractors over a grid can be clearly observed.

This paper carries out a further cryptanalysis of two Lorenz-based masking secure communication systems, which have been recently attacked by a high-pass filter. As demonstrated with our simulations, high-pass filter attack works well only when the covered information signal is monotonic. However, with an adaptive observer, it is still possible to coarsely obtain the information signal and correctly identify the system user-defined parameters if a multitonic information signal is transmitted, making the security of these two systems questionable.

A novel chaotic peak current-mode boost converter is proposed. By deriving its corresponding current mapping function, a thorough analysis of its chaotic behavior is carried out. As demonstrated both in simulations and experiments, the proposed design can effectively reduce electromagnetic interference and suppress ripples of the converter's output, resulting in a better design for power supplies.

In this paper, a new approach for synchronization of complex dynamical networks is proposed based on state observer design. Unlike the common diagonally coupling networks, where full state coupling is typically needed between two nodes, here it is suggested that only a scalar coupling signal is required to achieve network synchronization. Some conditions for synchronization, in the form of an inequality, are established based on the Lyapunov stability theory, which can be transformed to a linear matrix inequality and easily solved by a numerical toolbox. Two typical dynamical network configurations, i.e., global coupling and nearest-neighbor coupling, with each node being a modified Chua's circuit, are simulated. It is demonstrated that the proposed scheme is effective in achieving the expected chaos synchronization in the complex network

In this paper, a new scheme based on integral observer approach is designed for a class of chaotic systems to achieve synchronization. Unlike the proportional observer approach, the proposed scheme is demonstrated to be effective under a noisy environment in the transmission channel. Based on the Lyapunov stability theory, a sufficient condition for synchronization is derived in the form of a Lyapunov inequality. This Lyapunov inequality is further transformed into a linear matrix inequality (LMI) form by using the Schur theorem and some matrix operation techniques, which can be easily solved by the LMI toolboxes for the design of suitable control gains. It is demonstrated with the Murali-Lakshmanan-Chua system that a better noise suppression and a faster convergence speed can be achieved for chaos synchronization by using this integral observer scheme, as compared with the traditional proportional observer approach.

This brief presents a simple technique using a sinusoidal parameter perturbation control input to drive a unified chaotic system to hyperchaotic. The original chaotic system is a three-dimensional autonomous system that has a broad spectrum of chaotic behaviors with the Lorenz and the Chen systems as two extremes of the spectrum. The control input is a simple sinusoidal function cos(/spl omega/t) with a constant parameter /spl omega/. The hyperchaotic system is not only demonstrated by computer simulations but also verified with bifurcation analysis and implemented via an electronic circuit.

A hybrid genetic approach is proposed for container loading in order to meet the up-to-date customer requirements in the logistics industry. Container loading is usually modeled as a three-dimensional packing problem which is known to be NP-complete. By combining an order-based genetic algorithm with a novel heuristic placement method, the complicated and highly constrained packing problem is transformed into a simple permutation problem with a much smaller searching domain. It is guaranteed that every box is stable after placement inside the container. From the simulation results, it is demonstrated that optimal results can be duly obtained in a reasonably short period of time.

In this paper, a simple control method is proposed for stabilizing unstable equilibria of two typical classes of chaotic systems. For piecewise-linear chaotic systems, such as Chua's circuit, the control parameters can be selected via the pole placement technique from the linear control theory. For general nonlinear chaotic systems with continuously differentiable nonlinearities, particularly polynomial chaotic systems such as the Ro/spl uml/ssler system, Lorenz system, Chen's system, and the modified Chua's circuit with cubic nonlinearity, the control parameters can be chosen according to the pole placement technique and some additional theories of nonlinear ordinary differential equations. The criteria for the design of the control parameters are also investigated. This method is demonstrated to be highly robust against system parametric variations. To verify the effectiveness of the method, it is applied to both the original and the modified chaotic Chua's circuits, where satisfactory control performance is observed in simulations.

A hybrid genetic approach is proposed for the cutting operation in the clothing industry. Garment cutting is a typical strip-packing problem, which is considered to be NP-complete. With a combination of genetic algorithm (GA) and a novel heuristic algorithm, "lowest-fit-left-aligned," the cutting problem is transformed into a simple permutation problem which can be effectively solved by the GA and the searching domain is greatly reduced. From the simulation results, it is demonstrated that the optimal results can be obtained in a reasonably short period of time.

In this brief, the state PI regulator method is introduced for stabilizing unstable equilibrium points and tracking set-point targets for a class of chaotic systems. Based on the theory of nonlinear ordinary dif- ferential equations, a new criterion is derived for designing the controller gains for stabilization and tracking, in which control parameters can be se- lected via the pole placement technique of linear control theory. More im- portantly, according to our numerical studies, this method is robust against system parametric variations, can strongly reject external constant dis- turbances, and possesses an attractive low-frequency-disturbance response property. The design method is applied to the chaotic Lorenz system and Chua's circuit with a cubic nonlinearity, showing satisfactory simulation results.

A new approach for generating n-scroll attractors is introduced. It is demonstrated that n-scroll attractors can be generated using a simple sine or cosine function. A guideline is given so that a different number of scrolls can be designed easily by modifying two variables in the function. An electronic circuit is also designed for the implementation and the observation of a 9-scroll attractor is reported for the first time.