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real-time mobile robot teleoperation via Internet based on predictive control

中国高等学校学术文摘·机械工程 2008年第3期3卷 299-306页

作者： Shihua WANG Bugong XU YunHui LIU Yeming ZHOU Laboratory of Real-Time Control Through Internet and Fieldbuses College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China Naval Arms Command Academy of Guangzhou Guangzhou 510430 China Laboratory of Real-Time Control Through Internet and Fieldbuses College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China Naval Arms Command Academy of Guangzhou Guangzhou 510430 China Department of Automation and Computer Aided Engineering The Chinese University of Hong Kong Shatin N.T. HK China

A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the mas-ter and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay- jitter, a new data buffer scheme is per-formed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of tele-operation. The usefulness and effectiveness of the pro-posed method and system are proven by teleoperation experiments via the internet over a long distance.

关键词： teleoperation internet robots predictive con-trol delay algorithm

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Comparison of DE and PSO for generator maintenance scheduling

Comparison of DE and PSO for generator maintenance schedulin...

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IEEE Swarm Intelligence Symposium, SIS

作者： Y. Yare G. K. Venayagamoorthy Real-Time and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

This paper presents a comparison of a differential evolution (DE) algorithm and a modified discrete particle swarm optimization (MDPSO) algorithm for generating optimal preventive maintenance schedules for economical and reliable operation of a power system, while satisfying system load demand and crew constraints. The DE, an evolutionary technique and an optimization algorithm utilizes the differential information to guide its further search, and can handle mixed integer discrete continuous optimization problems. Discrete particle swarm optimization (DPSO) is known to effectively solve large scale multi-objective optimization problems and has been widely applied in power systems. Both the DE and MDPSO are applied to solve a multi-objective generator maintenance scheduling (GMS) optimization problem. The two algorithms generate feasible and optimal solutions and overcome the limitations of the conventional methods including extensive computational effort, which increases exponentially as the size of the problem increases. The proposed methods are tested, validated and compared on the Nigerian power system.

关键词： Power system reliability Scheduling algorithm Particle swarm optimization Power systems Power generation Preventive maintenance Power system economics Power generation economics Large-scale systems Processor scheduling

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CARBON REDUCTION POTENTIAL WITH INTELLIGENT CONTROL OF POWER SYSTEMS

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IFAC Proceedings Volumes 2008年第2期41卷 13952-13957页

作者： Ganesh K. Venayagamoorthy Gabriele Braband Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA Simmons & Simmons Dusseldorf Germany

Climate change caused by anthropogenic greenhouse gas (GHG) emissions such as carbon dioxide (CO 2 ) is now widely accepted as a real condition that has potentially serious consequences for human society and industries need to factor this into their strategic plans. One salient planning assumption is that energy - essential for every activity - will become more expensive relative to other inputs. Economic growth does not have to be linked to an increase of GHG emissions and can be attained in addition to the usage of renewable energy sources by using energy efficiency technologies for power system generation, transmission, and distribution. The development of intelligent energy-efficient control technologies will both soften negative effects of the climate change on the economy and enhance energy security. This paper outlines the significant carbon reduction potential with intelligent control and optimization techniques applied to power system generation and transmission systems with and without wind farms.

关键词： Intelligent control Economics Emissions Optimization Power systems

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Software architecture of the Autonomous Mobile Outdoor Robot AMOR

Software architecture of the Autonomous Mobile Outdoor Robot...

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IEEE Symposium on Intelligent Vehicle

作者： Klaus-Dieter Kuhnert Institute of Real-Time Learning Systems Department of Electrical Engineering and Computer Science University of Siegen Germany

Even if outdoor robotics is gaining increasing interest, universal systems are rare to find up to now. One of them is the autonomous mobile outdoor robot (AMOR), which operates in rough terrain under arbitrary weather condition. This paper presents its software architecture and some performance figures. The whole system is designed by a modular and layered paradigm, to allow for easy reconfiguration and adaptation to new tasks. Elementary behaviours act as the fundament, which delivers the basic abilities and secures the robot. Model based components are utilized for more intelligent tasks like obstacle avoidance and local/global path planning. Robust operation in complex terrain is achieved by combining a multitude of sensors. The software architecture unifies them by introducing a virtualisation layer, which hides all hardware specific consideration from the application programmer. This way the overall system configuration can be easily adapted to the actual task without changing the high level software. Above the medium layer an object oriented system has been implemented, that is able to localise, navigate and avoid obstacles in rough terrain. The overall performance of the system has been proven by winning the first price in autonomous driving in the European Land Robot Trial (ELROB 2007) for urban and non-urban terrain. Details of the performance are given in the results.

关键词： Vehicles

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Concept and implementation of a software system on the Autonomous Mobile Outdoor Robot AMOR

Concept and implementation of a software system on the Auton...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Klaus-Dieter Kuhnert Institute of Real-Time Learning Systems Department of Electrical Engineering and Computer Science University of Siegen Germany

The paper describes the software architecture of an autonomous mobile outdoor robot (AMOR). The robot is intended for robust operation in heavy terrain under arbitrary weather condition. The software is implemented in a layered architecture, possessing behaviour based and model based components. The multitude of different sensors is unified by a virtualisation layer, which allows easy reconfiguration and utilisation by the application programmer. The higher levels of the software system realise localisation, navigation and obstacle avoidance. The overall performance of the system has been proven by winning the first prize in autonomous driving in the European land robot trial (ELROB 2007) for urban and non- urban terrain.

关键词： Robots Sensors Vehicles Sensor systems Robustness Distance measurement Planning

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A differential evolution approach to optimal generator maintenance scheduling of the nigerian power system

A differential evolution approach to optimal generator maint...

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IEEE General Meeting Power& Energy Society

作者： Y. Yare G. K. Venayagamoorthy Real-Time and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

The goal of optimal generator maintenance scheduling is to evolve optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. In this paper, the differential evolution (DE), an evolutionary computation algorithm that utilizes the differential information to guide its further search, is applied to effectively solve the generator maintenance scheduling (GMS) optimization problem. The proposed method can handle mixed integer discrete continuous optimization problems. Results are presented with the DE algorithm on two different case studies for Nigerian power system.

关键词： Maintenance engineering Power systems Optimization Optimal scheduling Power system dynamics Generators Evolution (biology)

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Merge-by-Wire: Algorithms and System Support

Merge-by-Wire: Algorithms and System Support

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real-time Systems Symposium (RTSS)

作者： Vipul Shingde Gurulingesh Raravi Ashish Gudhe Prakhar Goyal Krithi Ramamritham Embedded Real-Time Systems Laboratory Department of Computer Science and Engineering Indian Institute of Technology Bombay

Automakers are trying to make vehicles more intelligent and safe by embedding processors which can be used to implement ldquoby-wirerdquo applications for taking smart decisions on the road or assisting the driver in doing the same. Given this proliferation, there is a need to minimize the computing power required without affecting the performance and safety of the applications. The latter is especially important since these by-wire applications are distributed and real-time in nature and involve deadline bound computations on critical data gathered from the environment. These applications have stringent requirements on the freshness of data items and completion time of the tasks. Our work studies one such safety-related automotive application namely, automatic merge control (AMC) which ensures safe vehicle maneuver in the region where two or more roads *** our contributions, we (i) propose two merge algorithms for amc: head of the lane (HoL) and all feasible sequences (AFS) (ii) demonstrate how DSRC-based wireless communication protocol can be leveraged for the development of AMC (iii) present a real-time approach towards designing AMC by integrating mode-change and real-time repository concepts for reducing the processing power requirements and (iv) provide a scheduling strategy to meet AMC taskspsila timing requirements. Simulations and implementation on robotic vehicular platforms demonstrate the advantages of using our approach for constructing merge-by-wire systems.

关键词： Intelligent vehicles Road vehicles Vehicle safety Vehicle driving Distributed computing Automotive applications Automatic control Communication system control Scheduling algorithm Wireless communication

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Implementation of a PSO based online design of an optimal excitation controller

Implementation of a PSO based online design of an optimal ex...

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IEEE Swarm Intelligence Symposium, SIS

作者： Chuan Yan Ganesh K. Venayagamoorthy Keith A. Corzine Real-time Power and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Real-timePower and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

The Navypsilas future electric ships will contain a number of pulsed power loads for high-energy applications such as radar, railguns, and advanced weapons. This pulse energy demand has to be provided by the ship energy sources, while not impacting the operation of the rest of the system. It is clear from studies carried out earlier that disturbances are created at the generator ac bus. This paper describes an online design and laboratory hardware implementation of an optimal excitation controller using particle swarm optimization (PSO) to minimize the effects of pulsed loads. The PSO algorithm has been implemented on a digital signal processor. laboratory results show that the PSO designed excitation controller provides an effective control of a generatorpsilas terminal voltage during pulsed loads, restoring and stabilizing it quickly.

关键词： Optimal control Marine vehicles Laboratories Voltage control Radar applications Railguns Weapons AC generators Hardware Particle swarm optimization

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Distributed Resource Kernels: OS Support for End-To-End Resource Isolation

Distributed Resource Kernels: OS Support for End-To-End Reso...

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IEEE Symposium on real-time and Embedded Technology and Applications

作者： Karthik Lakshmanan Raj Rajkumar Real Time and Multimedia Systems Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

The notion of resource reservation for obtaining real-time scheduling guarantees and enforcement of resource usage has gained strong support in recent years. However, much work on resource reservation has primarily focused on single-processor systems. In this paper, we propose the distributed resource kernel frame wo rk to deploy distributed real-time applications with end-to-end timing constraints, and to efficiently enforce and monitor their usage. Modern distributed real-time systems host multiple applications, where each application can span two or more processors. Timing bugs in one distributed application can affect the timing properties of other applications in the system. Our framework introduces the abstraction of a distributed resource container as an isolated virtual operating environment for a distributed real-time application. We have implemented this framework by extending our open-source single- node Linux/RK platform (R. Rajkumar et al., 1998). A deployment and monitoring tool called dMon is also provided. We evaluate the framework's ability to provide timing guarantees by stress-testing the system using the Distributed Hartstone benchmarks. An audio processing pipeline is then used to illustrate the temporal isolation support provided by the Distributed RK framework. The distributed container abstraction can also be extended in the future to support security and fault-tolerance attributes.

关键词： Kernel Timing Containers real time systems computer bugs Open source software Linux Pipelines Security Fault tolerance

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Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions

Intelligent Scheduling of Hybrid and Electric Vehicle Storag...

引用

IEEE Energy 2030 Conference, ENERGY

作者： Chris Hutson Ganesh Kumar Venayagamoorthy Keith A. Corzine Real-Time Power and Intelligent Systems (RTPIS) Laboratory mDepartment of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

This paper proposes an intelligent method for scheduling usage of available energy storage capacity from plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV). The batteries on these vehicles can either provide power to the grid when parked, known as vehicle-to-grid (V2G) concept or take power from the grid to charge the batteries on the vehicles. A scalable parking lot model is developed with different parameters assigned to fleets of vehicles. The size of the parking lot is assumed to be large enough to accommodate the number of vehicles performing grid transactions. In order to figure out the appropriate charge and discharge times throughout the day, binary particle swarm optimization is applied. Price curves from the California ISO database are used in this study to have realistic price fluctuations. Finding optimal solutions that maximize profits to vehicle owners while satisfying system and vehicle owners constraints is the objective of this study. Different fleets of vehicles are used to approximate varying customer base and demonstrate the scalability of parking lots for V2G. The results are compared for consistency and scalability. Discussions on how this technique can be applied to other grid issues such as peaking power are included at the end.

关键词： Intelligent vehicles Hybrid electric vehicles Battery powered vehicles Particle swarm optimization Iterative algorithms USA Councils Processor scheduling Energy storage Scalability Wind energy

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