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IEEE International Conference on Automation Science and engineering (CASE)

作者： Kevin K. Leung Garratt Gallagher Robotics Autonomous Systems and Controls Laboratory (RASCAL) Department of Mechanical and Aeronautical Engineering University of California Davis USA Department of Electrical and Computer Engineering Robotics Autonomus Systems and Control Laboratory (RASCAL) Department of Mechanical and Aeronautical Engineering University of California Davis USA

In this paper, we propose a simultaneous localization and map-building (SLAM) strategy to explore unknown environment. Multiple robots are deployed in unknown area and required to localize each other accurately while exploring. Instead of relying on active obstacle detector, we propose a method of exploration which uses only tactile sensors and inter-robot distance measurements. To avoid dead-reckoning and odometry errors, an observer-explorer based routine is adopted. A dynamic spanning tree structure is implemented for multi-robot coordination. Parent (observer) nodes monitor the distances of their children (explorer) nodes. In order to promote completeness of the map, the reconfigurable spanning tree structure favors unexplored area implicitly. An online behavior-based finite state machine drives the configuration of the structure. Our exploration scheme allows the differentiation between robots and obstacles or boundaries. When an obstacle or boundary is detected, it is recorded on a map that is shared with all other robots. The proposed strategy is simulated and results are presented.

关键词： Tree data structures Robot kinematics Robot sensing systems Simultaneous localization and mapping robotics and automation Distance measurement Automata Service robots Global Positioning System Costs

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Editorial: Knowledge engineering, semantics, and signal processing in audio - visual information retrieval

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IEEE Transactions on Circuits and systems for Video Technology 2007年第3期17卷 257-258页

作者： Izquierdo, Ebroul Zhang, Jian Sikora, Thomas Huang, Thomas S. Department of Electrical Engineering Queen Mary University of London London El 4NS United Kingdom Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Communication Systems Group Technical University Berlin Berlin Germany ITG University of Illinois at Urbana-Champaign United States Department of Electrical and Computer Engineering Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Institute for Advanced Science and Technology United States Institute's Major Research Theme Human Computer Intelligent Interaction National Academy of Engineering Chinese Academies of Engineering and Sciences China International Association of Pattern Recognition Optical Society of American United States

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关键词： Special issues and sections Knowledge engineering Information retrieval Audio-visual systems

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A Novel Impedance Measurement Technique for Power Electronic systems

A Novel Impedance Measurement Technique for Power Electronic...

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Annual IEEE Conference on Power Electronics Specialists (PESC)

作者： Peng Xiao Ganesh Venayagamoorthy Keith Corzine Real-Time Power and Intelligent Systems Laboratory Electrical and Computer Engineering Department University of Missouri Rolla Rolla MO USA

When designing and building power systems that contain power electronic switching sources and loads, system integrators must consider the frequency-dependent impedance characteristics at an interface to ensure system stability. Stability criteria have been developed in terms of source and load impedance for both dc and ac systems and it is often necessary to measure system impedance through experiments. Traditional injection-based impedance measurement techniques require multiple online tests which lead to many disadvantages. The impedance identification method proposed in this paper greatly reduces online test time by modeling the system with recurrent neural networks. The recurrent networks are trained with measured signals from the system with only one injection. The measurement and identification processes for dc and three-phase ac interfaces are developed. Simulation tests demonstrate the effectiveness of this new technique.

关键词： Impedance measurement Power electronics Power system stability Stability analysis Frequency measurement System testing Admittance Power system measurements Recurrent neural networks Power system simulation

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Optimal scheduling of generator maintenance using modified discrete particle swarm optimization

Optimal scheduling of generator maintenance using modified d...

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iREP Symposium on Bulk Power System Dynamics and Control

作者： Yusuf Yare Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems (RTPIS) Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

This paper presents a modified discrete particle swarm optimization (PSO) based technique for generating optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. While GA and other analytical methods might suffer from premature convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. PSO is known to effectively solve large scale multi-objective optimization problems. Here, a modified discrete PSO approach is proposed for the GMS optimization problem in order to overcome the limitations of the conventional methods and come up with a feasible and an optimal solution.

关键词： Optimal scheduling Particle swarm optimization Power system reliability Power generation Preventive maintenance Power system economics Power generation economics Power system analysis computing Convergence Large-scale systems

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Making the power grid more intelligent

Making the power grid more intelligent

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iREP Symposium on Bulk Power System Dynamics and Control

作者： Salman Mohagheghi Ronald G. Harley Ganesh K. Venayagamoorthy School of Electrical and Computer Engineering Georgia Institute of Technology Intelligent Power Infrastructure Consortium Atlanta GA USA Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory University of Missouri Rolla MO USA

Summary form only given. This paper focuses on the applications of intelligent techniques for improving the performances of the power system controllers. intelligent control techniques lay the foundation of the next generation of nonlinear controllers and have the advantage of further improving the controller's performance by incorporating heuristics and expert knowledge into its design. Most of these techniques are independent of any mathematical model of the power system, which proves to be a considerable advantage.

关键词： Power grids Power system modeling Control systems Power system dynamics Power system control Power systems Power system reliability intelligent networks Humans Three-term control

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Adaptive Critic Design Based Neuro-Fuzzy Controller for a Static Compensator in a Multimachine Power System

Adaptive Critic Design Based Neuro-Fuzzy Controller for a St...

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IEEE General Meeting Power& Energy Society

作者： Salman Mohagheghi Ganesh K. Venayagamoorthy Ronald G. Harley School of Electrical and Computer Engineering Georgia Institute of Technology Intelligent Power Infrastructure Consortium Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Summary form only given. This paper presents a novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks and fuzzy logic. The action dependent heuristic dynamic programming (ADHDP), a member of the adaptive critic designs (ACD) family, is used for the design of the STATCOM neuro-fuzzy controller. This neuro-fuzzy controller provides optimal control based on reinforcement learning and approximate dynamic programming, and can effectively perform in the presence of noise and uncertainties. Using a proportional-integrator approach the proposed controller is capable of dealing with actual rather than deviation signals. The STATCOM is connected to a multimachine power system in order to provide voltage support during the steady state performance of the power system and also improve the dynamic stability of the network during faults and disturbances. Two multimachine power systems are considered in this study: a 10-bus 2-generator system and a 45-bus 10-generator system, where the latter is a section of the Brazilian power grid. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller in large scale faults as well as small disturbances.

关键词： Programmable control Adaptive control Control systems STATCOM Power systems Power system dynamics Power system stability Optimal control Automatic voltage control Power system faults

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Neural-network-based intelligent control for improving dynamic performance of FACTS devices

Neural-network-based intelligent control for improving dynam...

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iREP Symposium on Bulk Power System Dynamics and Control

作者： Wei Qiao Ronald G. Harley Ganesh K. Venayagamoorthy Intelligent Power Infrastructure Consortium School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Flexible AC transmission system (FACTS) devices are widely recognized as powerful controllers to improve the dynamic performance and stability of power systems. The standard FACTS controllers are linear controllers designed around a specific operating point from a linearized system model with fixed parameters. However, at other operating points their performance degrades. Neural-network-based nonlinear intelligent control offers an attractive approach to overcome the drawbacks of the linear controllers. This paper presents two different neural-network-based intelligent control architectures, i.e., indirect adaptive neurocontrol and adaptive critic design based optimal neurocontrol, for designing the external control of an SSSC FACTS device. Simulation studies are carried out to evaluate the proposed nonlinear intelligent controllers on single machine infinite bus as well as multi-machine power systems. Results show that the proposed intelligent controls improve the dynamic performance of the SSSC and the associated power network.

关键词： intelligent control Power system dynamics Flexible AC transmission systems Power system stability Power system modeling Programmable control Adaptive control Power system simulation Control systems Nonlinear dynamical systems

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Swarm Intelligence for Transmission System Control

Swarm Intelligence for Transmission System Control

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IEEE General Meeting Power& Energy Society

作者： G. K. Venayagamoorthy R. G. Harley Real Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Many areas related to power system transmission require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. This paper highlights the application of swam intelligence techniques for solving some of the transmission system control problems.

关键词： Particle swarm optimization Control systems Power system analysis computing Power systems Power system stability Birds Marine animals Educational institutions Ant colony optimization Nonlinear control systems

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DHP-Based Wide-Area Coordinating Control of a Power System with a Large Wind Farm and Multiple FACTS Devices

DHP-Based Wide-Area Coordinating Control of a Power System w...

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International Joint Conference on Neural Networks (IJCNN)

作者： Wei Qiao Ganesh K. Venayagamoorthy Ronald G. Harley Intelligent Power Infrastructure Consortium (IPIC) in the School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory in the Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area monitor and wide-area coordinating neurocontroller (WACNC), based on wide-area measurements, for a power system with power system stabilizers, a large wind farm, and multiple flexible ac transmission system (FACTS) devices. The wide-area monitor is a radial basis function neural network (RBFNN) that identifies the input-output dynamics of the nonlinear power system. Its parameters are optimized through a particle swarm optimization (PSO) based method. The WACNC is designed by using the dual heuristic programming (DHP) method and RBFNNs. It operates at a global level to coordinate the actions of local power system controllers. Each local controller communicates with the WACNC, receives remote control signals from the WACNC to enhance its dynamic performance, and therefore helps improve system-wide dynamic and transient performance.

关键词： Power system control Control systems Power systems Wind farms Power system dynamics Power system measurements Monitoring Flexible AC transmission systems Power system transients Power industry

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Towards Content Oriented Integration of Product and Robot System Models

Towards Content Oriented Integration of Product and Robot Sy...

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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Laszlo Horvath Imre J. Rudas Karel Jezernik John von Neumann Faculty of Informatics Budapest Technology Institute of Intelligent Engineering Systems Budapest Hungary Faculty of Electrical Engineering and Computer Science Institute of Robotics University of Maribor Maribor Slovenia

An approach and method to integrate virtual engineering and robot systems is introduced. The main idea is extended application of the principle of shape aspect that is well-proven in part modeling. Shape intensive robot system is engineered by using of shape modeling. Shapes are connected by special aspects in a shape aspect oriented model system. The main purpose of the proposed approach and method is better communication between product modeling and robot related engineering. Associativity definitions integrate part level functions into product level functions while behaviors and adaptivities are also handled as aspects. Paper starts with introduction and comparison of classical industrial product modeling and the proposed integrated product and robot system modeling. Following this, extended application of shape aspects and definition of connective aspects are detailed. Finally, implementation in open architecture industrial modeling systems is explained and future work is outlined.

关键词： Service robots systems engineering and theory robotics and automation intelligent robots Solid modeling Informatics Shape control computer aided manufacturing Logistics electrical products industry

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