Yingze Yang

Effect of deposition and annealing temperature on properties of ZAO/Cu/ZAO multilayers

Abstract Transparent conductive multilayers consisting of a Cu layer sandwiched between Al doped zinc oxide layers were fabricated on conventional glass substrates by direct current magnetron sputtering. The effect of deposition and annealing temperature on the properties of these multilayers was investigated. The multilayer deposited at 100°C owned the maximum figure of merit of 2·65×10−2 Ω−1 with an average transmittance of 86·64% and a resistivity of 9·72×10−3 Ω cm. The crystallinity and photoelectric properties of multilayers were improved by post annealing treatment. The multilayer deposited at 100°C and post-annealed at 400°C resulted with a resistivity of 8·64×10−3 Ω cm and an average transmittance of 88·33%, and the figure of merit achieved to 3·61×10−2 Ω−1.

A fast handover scheme based on multiple mobile router cooperation for a train-based mobile network

True broadband access for high-speed train passengers has become a new trend in the world. To support the newly emerged mobile applications effectively, the mobile networks handover latency and packet losses during handover need to be as small as possible. To address this issue, a fast handover scheme based on multiple mobile router cooperation for mobile networks is proposed in this paper. Its basic idea is to take advantage of the features of the fixed line and routing information in the railway passenger transportation system in order to configure the mobile routers next care-of-address (CoA) in advance, thus reducing the new CoA configuration time. Moreover, two or more mobile routers spatially separated by a certain distance are configured on the railway train that enables different mobile routers to access different subnets during handover and cooperatively receive packets from each other. The overlapped reception of packets from deferent subnets makes the packet loss independent of the handover latency, and reduces packet losses during handover. The mathematical analysis and simulation experiments are presented to show the feasibility and effectiveness of the proposed scheme.

Locomotive Brake Control Method Based on T-S Fuzzy Modeling Predictive Control

To achieve braking control of locomotive brake control system (LBCS) accurately and steadily under high nonlinearity various time delay condition, a locomotive brake control method based on T-S fuzzy modeling predictive control (MPC) is proposed. Firstly, the paper uses fuzzy clustering method (FCM) to initial parameters, and uses back-propagation algorithm to rectify rectified its premise parameters by learning off-line. The consequent parameters of the fuzzy rules are self-learning online by recursive least square method with the forgetting factor. By introducing the conception of quality satisfying degree to rectify forgetting factor, the paper can precision and construct T-S modeling.Secondly, the paper uses MPC to control LBCS. The fuzzy genetic algorithm (FGA) of importing excellent subpopulation migrating strategy is used as rolling optimization (RO) method to reduce the influence of the model parameters, the noise coupling and the random interference of this system. It can improve control capability and accelerate quicken the speed of convergence. At last, Simulation and practical application in new generation locomotive brake system show that this improved method is effective.

Optimal Operation of High-Speed Trains Using Hybrid Model Predictive Control

The high-speed train operation process is highly nonlinear and has multiple constraints and objectives, which lead to a requirement for the automatic train operation (ATO) system. In this paper, a hybrid model predictive control (MPC) framework is proposed for the controller design of the ATO system. Firstly, a piecewise linear system with state and input constraints is constructed through piecewise linearization of the high-speed train’s nonlinear dynamics. Secondly, the piecewise linear system is transformed into a mixed logical dynamical (MLD) system by introducing the auxiliary binary variables. For the transformed MLD system, a hybrid MPC controller is designed to realize the precise control under hard constraints. To reduce the online computation complexity, the explicit control law is computed offline by employing the mixed-integer linear programming (MILP) technique. Simulation results validate the effectiveness of the proposed method.

Mathematical modeling of electrical controlled pneumatic brake

Inconsistent brake forces will aggravate impacts of collision between adjacent freight cars with different car types and load weights, especially in rigid connection mode which is widely used in Chinese freight lines. As its designed with complex components and various operation modes the pneumatic brake system is a highly nonlinear one, it is hard to model and analyze its instantaneous state. In this paper, a mathematic model of the pneumatic brake is proposed. According to real-time operation mode of ECP system and brake stage of freight train, tracking object is dynamically adjusted to fit complex railway conditions. Finally, simulation results verify the astringency of this proposed algorithm, and shows collisions of ECP brake are decreased and real-time performance is improved.

An energy-based nonlinear pressure observer for electronically controlled pneumatic brake fault diagnosis

As widely used in the heavy-haul combined trains, electronically controlled pneumatic(ECP) brake is a highly nonlinear system. Heavy-haul combined train consists of variant freight trucks with different types and different load weights. When operating with brake mode, inconsistent braking forces will aggravate impacts of collisions between adjacent freight cars, especially uncertainty faults occur and the trucks in rigid connection mode. Therefore, it is necessary to conduct online fault diagnosis for ECP brakes. In this paper, an Lyapunov-based globally stable pressure observer for ECP brake is proposed. Firstly, according to the output value of the observer, a residual generator is designed and residual signals are evaluated with the Generalized Likelihood Ratio(GLR) method. Secondly, fault diagnosis can be achieved by GLR when systems faults happened. Finally, experimental results demonstrate and validate effectiveness of the proposed observer and algorithm.

Decentralized event-triggered cooperative control for multi-agent systems with uncertain dynamics using local estimators☆

Abstract This paper presents a decentralized event triggered cooperative control design for uncertain multi-agent systems under limited communication resources. A local estimator is employed by each agent to generate self-state estimates. The estimated states are directly used in the consensus control design, and the estimator parameters are used in the event condition design. Once an event is triggered, the local estimator is repeatedly reset to its corresponding real state values, such that it can stabilize the uncertain dynamical systems without knowing the exact system model parameters. A theorem for this triggering condition is developed to provide stable thresholds that are robust to model uncertainties and guarantee the asymptotical stability by exploiting the M-matrix, algebraic graph theory and the Lyapunov method. It is rigorously proved that the overall system will achieve the consensus and has no zeno behavior under the introduced triggering condition. Simulation results are provided to show the effectiveness of the proposed decentralized event-triggered cooperative control strategy.

Actuator fault detection based on robust adaptive observer for CCBII Braking System

This paper presents a robust adaptive fault estimation design method to solve the problem of actuator fault estimation for CCBII Braking System with disturbances and model uncertainties. The proposed robust adaptive fault estimator which is based on an adaptive observer can improve the speed of fault estimation. By transforming the system model into a special coordinate basis (SCB) form, we can structure the desired observer. This transformation can achieve a decoupling between the fault estimates and the disturbances. As a result, the conventional adaptive observer is improved to enhance the speed of fault estimation through this decoupling. Simulation experiments of CCBII braking system are given to validate the effectiveness of the fault detection method.