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Geographical angular zone-based optimal resource allocation and efficient routing protocols for vehicular ad hoc networks

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IET INTELLIGENT TRANSPORT SYSTEMS 2018年第3期12卷 242-250页

作者： Madasamy, Bhuvaneswari Balasubramanian, Paramasivan Natl Engn Coll Dept Comp Sci & Engn Kovilpatti Tamil Nadu India

Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Owing to the absence of centralised management, there is pitfall in optimal resource allocation that leads ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming (SDP) is currently employed as a tool to analyse and solve network resource constraint and allocation issues of resources in VANET. The authors have considered this work as a geographic angular zone-based two-phase dynamic resource allocation problem with homogeneous and heterogeneous resource class. This work uses relaxed approximation-based SDP algorithm to generate optimal resource allocation strategies over time in response to past task completion status history. The second-phase resource allocation uses the observed outcome of the first-phase task completion to provide optimal viability decisions. They have also suggested an alternative solution called model predictive control algorithm (MPCA) that used approximation as a part to allocate resource over time in response to information on data transmission completion status. Simulation results show that the proposed schemes works significantly well for homogeneous resources.

关键词： vehicular ad hoc networks routing protocols intelligent transportation systems resource allocation stochastic programming dynamic programming predictive control routing protocols vehicular ad hoc networks VANET collaboration intelligent transportation SDP network resource constraint geographic angular zone-based two-phase dynamic resource allocation problem homogeneous resource class heterogeneous resource class relaxed approximation-based stochastic dynamic programming algorithm optimal resource allocation strategies task completion status history second-phase resource allocation first-phase task completion model predictive control algorithm MPCA data transmission completion status

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Unmanned aerial vehicle dynamic path planning in an uncertain environment

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ROBOTICA 2015年第3期33卷 611-621页

作者： Yao, Min Zhao, Min Nanjing Univ Aeronaut & Astronaut Nanjing Jiangsu Peoples R China

An unmanned aerial vehicle (UAV) dynamic path planning method is proposed to avoid not only static threats but also mobile threats. The path of a UAV is planned or modified by the potential trajectory of the mobile threat, which is predicted by its current position, velocity, and direction angle, because the positions of the UAV and mobile threat are dynamically changing. In each UAV planning path, the UAV incurs some costs, including control costs to change the direction angle, route costs to bypass the threats, and threat costs to acquire some probability to be destroyed by threats. The model predictive control (MPC) algorithm is used to determine the optimal or sub-optimal path with minimum overall costs. The MPC algorithm is a rolling-optimization feedback algorithm. It is used to plan the UAV path in several steps online instead of one-time offline to avoid sudden and mobile threats dynamically. Lastly, solution implementation is described along with several simulation results that demonstrate the effectiveness of the proposed method.

关键词： UAV Dynamic path planning model predictive control algorithm Mobile threats Uncertain environment

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Laser-based SLAM automatic parallel parking path planning and tracking for passenger vehicle

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IET INTELLIGENT TRANSPORT SYSTEMS 2019年第10期13卷 1557-1568页

作者： Song, Jie Zhang, Weiwei Wu, Xuncheng Cao, Haotian Gao, Qiaoming Luo, Suyun Shanghai Univ Engn Sci Coll Mech & Automot Engn Shanghai 201620 Peoples R China Hunan Univ State Key Lab Adv Design & Mfg Vehicle Body Changsha 410082 Hunan Peoples R China Guangxi Univ Sci & Technol Coll Automobile & Transportat Liuzhou 545006 Peoples R China

Automatic parking system (APS) plays an important role in alleviating drivers' burden and improving vehicle safety. This study proposes a laser-based simultaneous localisation and mapping (SLAM) automatic parallel parking and tracking control scheme, which include environment perception and reconstruction, parking path planning, and path following. First, the proposed approach selects short-range lidar to enlarge its perceptron on parking environment and senses available parking space to build neighbourhood mapping with the help of simultaneous localisation. The test evaluation indicates that laser-SLAM has achieved good performance for recognising free spaces. Then, scene-dependent B-spline parallel parking path planning algorithm is proposed to optimise the parking path curve and makes the path meet vehicle kinematics model constrains well, in which vehicle actuator's dynamic performance and parking path smoothness are taken as key attributes. The experiment results indicate that the designed parallel parking path is better smooth. At last, a path following control method based on model predictive control (MPC) algorithm is proposed. The authors built an intelligent vehicle APS platform, and the results indicate that the designed MPC algorithms has excellent robustness and can minimise the tracking error. All the proposed scheme is quantitatively evaluated using different parking scene simulation with satisfactory performance.

关键词： collision avoidance path planning SLAM (robots) mobile robots predictive control automobiles vehicle dynamics splines (mathematics) laser-based SLAM automatic parallel parking path planning passenger vehicle automatic parking system tracking control scheme environment perception reconstruction parking environment laser-SLAM scene-dependent B-spline parallel parking path parking path curve vehicle kinematics model designed parallel parking path model predictive control algorithm intelligent vehicle APS platform different parking scene simulation vehicle safety laser-based simultaneous localisation and mapping available parking space sensing

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Path planning of autonomous agricultural machineries in complex rural road

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JOURNAL OF ENGINEERING-JOE 2020年第6期2020卷 239-245页

作者： Cui, Jinbo Zhang, Xianfeng Fan, Xinmiao Feng, Wei Li, Ping Wu, Yu Chongqing Acad Agr Sci Chongqing Peoples R China Sichuan Normal Univ Coll Movie & Media Chengdu Peoples R China

This study mainly investigates the path planning and collision avoidance problem of autonomous agricultural machineries in the complex rural road. First, the grid model is used to build the global map of machineries and the particle swarm optimisation algorithm is used to search the global path. A non-linear dynamic inertia weight is introduced to avoid the local lock-up problem of traditional particle swarm optimisation. Then the artificial potential energy method for addressing the local collision problem is used, which is the sum of the attraction of the target point and the repulsion of the obstacles and the road boundary force. To solve the problem of the slip and roll of autonomous machinery caused by complex roads, a machinery dynamic model considering road curvature and topographic inclination is established, and the model predictive control algorithm is used to track the planned path. The simulation results show that proposed method can make the autonomous agricultural machinery driving safely and smoothly.

关键词： predictive control collision avoidance particle swarm optimisation agricultural machinery nonlinear dynamic inertia weight traditional particle swarm optimisation road boundary force autonomous machinery model predictive control algorithm autonomous agricultural machinery path planning collision avoidance problem particle swarm optimisation algorithm machinery dynamic model

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Nonlinear observer output-feedback MPC treatment scheduling for HIV

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BIOMEDICAL ENGINEERING ONLINE 2011年第1期10卷 1-16页

作者： Zurakowski, Ryan Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

Background: Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods: In previous work we have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results: The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions: The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback model predictive control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

关键词： model predictive control Nonlinear Observer Viral Load Measurement model predictive control algorithm Structure Treatment Interruption

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Wind power fluctuation mitigation based low-frequency oscillation

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The Journal of Engineering 2017年第13期2017卷 1299-1306页

作者： Yushu Sun Hua Ye Xiaozhe Sun Fufeng Miao Institute of Electrical Engineering Chinese Academy of Sciences Direct Current Power Grid Science and Technology Laboratory Haidian District Beijing 100190 People's Republic of China Sinopec Oilfield Service Shengli Corporation Tarim Branch Company Korla Xinjiang 841000 People's Republic of China State Grid Henan Power Company Economic and Technological Research Institute Department of Planning and Review Zhengzhou Henan 450052 People's Republic of China

Owing to the stochastic and intermittent of output power of wind farms, the large-scale grid-connected wind power could have a remarkable impact on the power system operation. In this study, wind power fluctuation (WPF) mitigation is achieved from the perspective of power system low-frequency oscillation (LFO). Firstly, in order to meet fluctuation mitigation requirement, model predictive control algorithm is applied to smooth WPF. Secondly, the Hilbert–Huang transform method is used to obtain the influences of wind power before and after smoothing on system LFO. In addition, wind power is decomposed into high, medium and low bands by empirical mode decomposition, and then the impacts of different bands wind power on system LFO are studied. Finally, the influences of wind power with different fluctuation rates on system LFO are analysed based on the WSCC 3-machine 9-bus power system, which provides a theoretical reference for smoothing WPF.

关键词： oscillations power grids wind power plants power system stability Hilbert transforms predictive control power generation control system LFO WSCC 3-machine 9-bus power system smoothing WPF empirical mode decomposition Hilbert-Huang transform method model predictive control algorithm smooth WPF fluctuation mitigation requirement power system low-frequency oscillation wind power fluctuation mitigation power system operation wind farms

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Integration of Production Planning and Real-Time Process control

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IFAC Proceedings Volumes 1991年第12期24卷 61-66页

作者： H. Nishitani I. Tamura E. Kunugita Department of Information & Computer Sciences Osaka University 1-1 Machikaneyama Toyonaka Osaka 560 Japan

Some computer control algorithms known as the model predictive control can treat the future information of desired trajectories of the controlled variables and measurable disturbances. Consequently, it can include both the feedback and feedforward control elements. This implies that the algorithm can be used as an interface between the non-real-time planning system of which emphasis is on the feedforward effects and the real-time control system of which emphasis is on the feedback effects.

关键词： Production control hierarchical system non-real-time planning real-time control interface model predictive control algorithm

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Computer-advised insulin infusion in postoperative cardiac surgery patients: a randomized prospective controlled multicenter trial

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Crit Care 2006年第SUPPL 1期10卷 P3-P3页

作者： J Cordingley J Plank J Blaha M Wilinska L Chassin C Morgan S Squire M Haluzik J Kremen S Svacina W Toller A Plasnik M Ellmerer R Hovorka T Pieber Royal Brompton Hospital London UK Medical University Graz Austria Charles University Hospital Prague Czech Republic Addenbrooke's Hospital Cambridge UK

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