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Periodic hypersonic cruise trajectory has been proved to be a feasible approach to low aerodynamic heating and fuel consumption. This kind of trajectory is solution of optimal control of hypersonic cruise vehicle. By this study, the features of the trajectory has been explained. Then the dynamic system has been simplified and divided into a 2-D automatic system and a 1-D non-automatic one. The 2-D automatic system describes the variation of flight-path angle and atmospheric density, and decides the periodicity and of the trajectory. The 1-D non-automatic system describes the variation of kinetic energy. On basis of this simplification, the mechanism of fuel consumption and alleviation of heating has been explained. Besides, the existence of singular arc of thrust coefficient has been analyzed. This work explains the mechanism of periodic hypersonic cruise trajectory. The features and the mechanism are suggestive in further trajectory design of hypersonic cruise vehicle.

Object of this work is hypersonic cruise vehicle which cruises at Mach number beyond 5 in atmosphere. Range of this vehicle is often restricted by the poor aerodynamic, propulsive and structural performances and severe persistent aerodynamic heating. To extend its range, optimal periodic cruise trajectory has been adopted herein to improve fuel efficiency and remit heat accumulation. The performance measure is a weighted combination of the two factors. The simulations show that the two factors are mutually contradicted with variation of weighting factor, and that improvement of aerodynamic heating is much more distinct than that of fuel efficiency. The study on single period is helpful to design the whole flight envelop in future research.

In this paper, we propose the pseudo multi-hop distributed consensus algorithm under directed communication topologies. The property and convergence rate of the pseudo multi-hop distributed consensus algorithm under directed communication topologies are analyzed, and the convergence conditions for the pseudo multi-hop distributed consensus algorithm is given. In particular, the convergence rate is determined by the spectral radius of the matrix depend on the communication topology. Finally, simulation results are provided to verify these analytical results.

In order to improve the accuracy of distributed consensus under quantized communication, in the paper, we firstly propose a modification to the probabilistically quantized distributed (PQDA) algorithm, and we update the state of every node by its state and the probabilistically quantized information of the adjacency nodes. Moreover, based on the modification, we propose a second-order modified probabilistically quantized algorithm. We analyze the performance and the mean square errors of the second-order modified probabilistic quantization distributed consensus, by analysis and simulation, the results show the second-order distributed consensus with modified probabilistic quantization fails to reach a consensus, but the mean square error is far smaller than that of the PQDA algorithm, and the curve chart of the new algorithm is similar to that of the distributed average consensus algorithm without distortion.

In order to improve the accuracy and the convergence rate of distributed consensus under quantized communication, in the paper, based on one-bit adaptive quantization scheme, we propose the second-order distributed consensus to update the state of every node by the present quantized values and the previous quantized values of the adjacency nodes. We analyze the convergence performance. The second-order distributed consensus with one-bit adaptive quantization achieves a consensus in a mean square sense, and the consensus is equal to the average of the initial states. Simultaneously, Simulations are done about the second-order distributed consensus based on one-bit adaptive quantization. Results show that the second-order distributed consensus algorithm based on one-bit adaptive quantization can reach an average consensus, and its convergence rate is higher than that of the first-order adaptive quantized distributed consensus algorithm, moreover, the mean square errors are smaller within the finite steps.

In order to improve the accuracy and the convergence rate of distributed consensus under quantized communication, in the paper, based on adaptive quantization scheme, we propose the fast second-order distributed consensus algorithm. We analyze the convergence performance. The fast second-order distributed consensus with adaptive quantization achieves a consensus in a mean square sense, and the consensus is equal to the average of the initial states. Simultaneously, Simulations are done about the fast second-order distributed consensus based on adaptive quantization. Results show that the fast second-order distributed consensus algorithm based on adaptive quantization can reach an average consensus, and its convergence rate is higher than that of the first-order adaptive quantized distributed consensus algorithm, moreover, the mean square errors are smaller within the finite steps.

In this paper, we analyze the pseudo two-hop distributed consensus algorithm with communication noise. If there is communication noise among agents, the convergence performance of distributed consensus algorithms degrades. Supposing that the communication noises are zero-mean Gaussian white noise, and the noises are irrelevant and independent in time and spatial, we analyze the convergence performance of the pseudo two-hop distributed consensus algorithm with noise, and calculate mean square errors and the upper bound of mean-square error of the pseudo two-hop distributed consensus algorithm. Finally, simulation results are provided to verify these analytical results.

In the paper, we analyze the distributed flocking algorithms with communication noise. Under Boid model, flocking algorithm with communication noise is easy to diverge. In order to improve the convergence performance of flocking algorithms with communication noise and overcome the impact brought by communication noise on flocking algorithm, in the paper, a distributed flocking algorithm based on SODCT distributed consensus algorithm is proposed. The second-order flocking algorithm under Boid model is analyzed, and simulations are done. Results show that the second-order distributed flocking algorithm can reach cohesion, and its convergence performance is better than that of the first-order distributed flocking algorithm, moreover, the impact of communication noise on the second-order flocking algorithm is smaller.

In the paper, we analyze the distributed flocking algorithms under virtual leader-follower model with communication time-delay. Under virtual leader-follower model, flocking algorithm can avoid diverging, but the performance of flocking algorithm with communication time-delay often degrades. In the paper, we analyze the impact brought by communication time-delay on the flocking algorithm when part agents can receive the information of the virtual leader, and simulations are done. Results show that the performance of distributed flocking algorithm depends on the number of agents that can receive the information of the virtual leader and the communication time-delay. Bigger is the number of agents that can receive the information of the virtual leader, better is the performance of flocking algorithms with communication time-delay.

In the paper, we address the problem of target tracking with quantized communication. While the probabilistic distribution function of the measurement is unknown, in order to simplify the calculations of target tracking system and improve the accuracy of estimation, we propose a Kalman filter under uniformly probabilistic quantization, and analyze the performance of the probabilistic quantization Kalman filter. Simulations results are provided to verify the performance of the target tracking system under uniformly probabilistic quantization.