10 results on '"Wang, Le Yi"'
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2. Two-Time-Scale Hybrid Traffic Models for Pedestrian Crowds.
- Author
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Wang, Qianling, Dong, Hairong, Ning, Bin, Wang, Le Yi, and Yin, George
- Abstract
This paper introduces new models to describe pedestrian crowd dynamics in a typical unidirectional environment, such as corridors, pathways, and railway platforms. Pedestrian movements are represented in a two-dimensional space that is further divided into narrow virtual lanes. Consequently, pedestrians either move in a lane following each other or change lanes, when it is desirable. Within this framework, the motions of pedestrians are modeled as a two-dimensional and two-time-scale hybrid system. A pedestrian’s movement along the crowd direction is labeled as the $x$ direction and modeled by a real-valued process, a solution of a differential equation in continuous time, the lane change is labeled as the $y$ direction. In contrast to the $x$ direction dynamics, the movements in the $y$ direction only happen at some time epoch. Although the movements are still on the same time horizon as the $x$ direction movements, with a slight abuse of notation and for simplicity and convenience, we use discrete time as the time indicator, and model the movements by a recursive equation taking values in a finite set. Under common assumptions of crowd movements, we prove that the crowd movements in the $x$ direction will converge to a uniform distance distribution and the convergence rate is exponential. Furthermore, by using a velocity-distance function to represent the common crowd and traffic congestion scenarios, we show that all pedestrians will asymptotically move with a uniform group speed. In the $y$ direction, when pedestrians naturally wish to change to faster lanes, we show that the numbers in each virtual lanes converge to a balanced distribution and hence achieves asymptotic consensus as shown typically in a crowd behavior. Stability and convergence analysis is carried out rigorously by using properties of circular matrices, stability of networked systems, and stochastic approximations. Simulation studies are used to demonstrate the main properties of our modeling approach and establish its usefulness in representing pedestrian dynamics. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
3. Optimal Power Management in DC Microgrids With Applications to Dual-Source Trolleybus Systems.
- Author
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Zhang, Di, Wang, Le Yi, Jiang, Jiuchun, and Zhang, Weige
- Abstract
This paper investigates optimal power management in dc microgrids, with its applications to dc dual-source trolleybus systems. High mobility of buses and their impact on power supply networks introduce challenging power management issues. This paper incorporates line power losses in power management strategies and introduces a new distributed optimal power management methodology. A multi-objective optimization model is developed. Using only neighborhood information exchange among feeder lines in the network, the new consensus-type control accommodates both feeder current allocation and power loss reduction with fast convergence. One critical finding of this paper is that our local recursive optimization algorithms achieve the global optimal solution asymptotically. Under random noise on information exchange, convergence and optimality of the proposed method are established rigorously. The power system configurations of the Beijing dual-source trolleybus system are used for simulation case studies on the new power management methods. Feasibility, accuracy, and comparison with global optimization results are demonstrated. [ABSTRACT FROM PUBLISHER]
- Published
- 2018
- Full Text
- View/download PDF
4. Impact of Communication Erasure Channels on Control Performance of Connected and Automated Vehicles.
- Author
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Nguyen, Thu, Wang, Le Yi, Yin, George, Zhang, Hongwei, Li, Shengbo Eben, and Li, Keqiang
- Subjects
- *
AUTONOMOUS vehicles , *WIRELESS communications , *AUTOMOTIVE transportation , *INTELLIGENT transportation systems , *MOBILE communication systems , *TELECOMMUNICATION systems - Abstract
Connected and automated vehicles mandate integrated design of communications and control to achieve coordination of highway vehicles. Random features of wireless communications introduce new types of uncertainties into networked systems and impact control performance significantly. Due to typical packet loss, erasure channels create random link interruption and switching in network topologies. This paper models such switching network topologies by Markov chains and derives their probability transition matrices from stochastic characterizations of the channels. Impact of communication erasure channels on vehicle platoon formation and robustness under a weighted and constrained consensus framework is analyzed. By comparing convergence properties of networked control algorithms under different communication channel features, we characterize some intrinsic relationships between packet delivery ratio and convergence rate. Simulation case studies are performed to verify the theoretical findings. [ABSTRACT FROM PUBLISHER]
- Published
- 2018
- Full Text
- View/download PDF
5. Robust consensus control by state-dependent dithers.
- Author
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Xu, Lijian, Wang, Le Yi, Yin, George, and Zheng, Wei Xing
- Abstract
This paper introduces a new method for enhancing robustness against communication uncertainties in consensus control by using a state and sampling-interval dependent dither in signal transmission. This method is based on the principle of Itô's formula for stochastic differential equation in which the diffusion term introduces a quadratic term in stability analysis. It is revealed that this feature can be utilized to provide robustness against communication multiplicative uncertainties, much beyond the ability of traditional feedback robustness design. Algorithms are introduced and their convergence properties are established. It is shown that appropriate design of the dithers can create a highly robust consensus control. Simulation results are used to illustrate the benefits of this method. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
6. Coordinated vehicle platoon control: Weighted and constrained consensus and communication network topologies.
- Author
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Wang, Le Yi, Syed, Ali, Yin, George, Pandya, Abhilash, and Zhang, Hongwei
- Abstract
This paper introduces a new method for enhancing highway safety and efficiency by coordinated control of vehicle platoons. One of our aims is to understand influence of communication network topologies and uncertainties on control performance. Vehicle deployment is formulated as a weighted and constrained consensus control problem. Algorithms are introduced and their convergence properties are established. The main advantages of the methods are demonstrated, including using local control to achieve a global deployment so that communication complexity is reduced; scalability to accommodate dynamic changes of the member vehicles and communication networks; robustness against road conditions and communication uncertainties. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
7. Sign-Regressor Adaptive Filtering Algorithms for Markovian Parameters.
- Author
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Yin, G. George, Hashemi, Araz, and Wang, Le Yi
- Subjects
ADAPTIVE filters ,MEAN square algorithms ,MATHEMATICS terminology ,MARKOV processes ,PARAMETER estimation ,DIFFERENTIAL equations ,MATHEMATICAL models - Abstract
This work is devoted to analyzing adaptive filtering algorithms with the use of sign-regressor for randomly time-varying parameters (a discrete-time Markov chain). In accordance with different adaption and transition rates, we analyze the corresponding asymptotic properties of the algorithms. When the adaptation rate is in line with the transition rate, we obtain a limit of a Markov switched differential equation. When the Markov chain is slowly changing the parameter process is almost a constant, and we derive a limit differential equation. When the Markov chain is fast varying, the limit system is again a differential equation that is an average with respect to the stationary distribution of the Markov chain. In addition to the limit dynamic systems, we obtain asymptotic properties of centered and scaled tracking errors. We obtain mean square errors to illustrate the dependence on the stepsize as well as on the transition rate. The limit distributions in terms of scaled errors are studied by examining certain centered and scaled error sequences. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
8. Real-Time Parameter Estimation of PMDC Motors Using Quantized Sensors.
- Author
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Obeidat, Mohammad A., Wang, Le Yi, and Lin, Feng
- Subjects
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REAL-time computing , *PERMANENT magnets , *DIRECT currents , *ELECTRIC motors , *PARAMETER estimation , *SIGNAL quantization - Abstract
Establishing real-time models for electric motors is important when capturing authentic dynamic behavior of the motors to improve control performance, enhance robustness, and support diagnosis. Quantized sensors are less expensive, and remotely controlled motors mandate signal quantization. Such limitations on observations introduce challenging issues in motor parameter estimation. This paper develops estimators for model parameters of permanent-magnet direct current (PMDC) motors using quantized speed measurements. A typical linearized model structure of PMDC motors is used as a benchmark platform to demonstrate the technology and its key properties and benefits. Convergence properties are established. Simulations and experimental studies are performed to illustrate potential applications of the technology. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
- View/download PDF
9. Enhanced Identification of Battery Models for Real-Time Battery Management.
- Author
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Sitterly, Mark, Wang, Le Yi, Yin, G. George, and Wang, Caisheng
- Abstract
Renewable energy generation, vehicle electrification, and smart grids rely critically on energy storage devices for enhancement of operations, reliability, and efficiency. Battery systems consist of many battery cells, which have different characteristics even when they are new, and change with time and operating conditions due to a variety of factors such as aging, operational conditions, and chemical property variations. Their effective management requires high fidelity models. This paper aims to develop identification algorithms that capture individualized characteristics of each battery cell and produce updated models in real time. It is shown that typical battery models may not be identifiable, unique battery model features require modified input/output expressions, and standard least-squares methods will encounter identification bias. This paper devises modified model structures and identification algorithms to resolve these issues. System identifiability, algorithm convergence, identification bias, and bias correction mechanisms are rigorously established. A typical battery model structure is used to illustrate utilities of the methods. [ABSTRACT FROM PUBLISHER]
- Published
- 2011
- Full Text
- View/download PDF
10. Asymptotic properties of consensus-type algorithms for networked systems with regime-switching topologies
- Author
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Yin, G., Sun, Yu, and Wang, Le Yi
- Subjects
- *
ASYMPTOTIC theory of system theory , *ALGORITHMS , *STOCHASTIC convergence , *APPROXIMATION theory , *MARKOV processes , *DIFFERENTIAL equations , *MATHEMATICAL models , *DISCRETE-time systems - Abstract
Abstract: This paper is concerned with asymptotic properties of consensus-type algorithms for networked systems whose topologies switch randomly. The regime-switching process is modeled as a discrete-time Markov chain with a finite state space. The consensus control is achieved by using stochastic approximation methods. In the setup, the regime-switching process (the Markov chain) contains a rate parameter in the transition probability matrix that characterizes how frequently the topology switches. On the other hand, the consensus control algorithm uses a stepsize that defines how fast the network states are updated. Depending on their relative values, three distinct scenarios emerge. Under suitable conditions, we show that when , a continuous-time interpolation of the iterates converges weakly to a system of randomly switching ordinary differential equations modulated by a continuous-time Markov chain. In this case a scaled sequence of tracking errors converges to a system of switching diffusion. When , the network topology is almost non-switching during consensus control transient intervals, and hence the limit dynamic system is simply an autonomous differential equation. When , the Markov chain acts as a fast varying noise, and only its averaged network matrices are relevant, resulting in a limit differential equation that is an average with respect to the stationary measure of the Markov chain. Simulation results are presented to demonstrate these findings. [Copyright &y& Elsevier]
- Published
- 2011
- Full Text
- View/download PDF
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