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2007 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Oliver Wulf Andreas Nuchter Joachim Hertzberg Bernardo Wagner Real Time Systems Group (RST) of the Institute for Systems Engineering Leibniz Universität Hannover Germany The Knowledge Based Systems Research Group Institute of Computer Science University of Osnabrück Germany

In the past many solutions for simultaneous localization and mapping (SLAM) have been presented. Recently these solutions have been extended to map large environments with six degrees of freedom (DoF) poses. To demonstrate the capabilities of these SLAM algorithms it is common practice to present the generated maps and successful loop closing. Unfortunately there is often no objective performance metric that allows to compare different approaches. This fact is attributed to the lack of ground truth data. For this reason we present a novel method that is able to generate this ground truth data based on reference maps. Further on, the resulting reference path is used to measure the absolute performance of different 6D SLAM algorithms building a large urban outdoor map.

关键词： Simultaneous localization and mapping Measurement Mobile robots Robot kinematics Robot sensing systems computer science Intelligent robots USA Councils Optimization methods

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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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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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Differential Evolution Approach for Reactive Power Optimization of Nigerian Grid System

Differential Evolution Approach for Reactive Power Optimizat...

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IEEE General Meeting Power& Energy Society

作者： G. A. Bakare G. Krost G. K. Venayagamoorthy U. O. Aliyu Abubakar Tafawa Balewa University Bauchi Nigeria Electrical Power Systems Institute University of Duisburg-Essen Duisburg Germany Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

The goal of reactive power dispatch is to minimize the system losses and improve the system voltage profiles at all times. This is achieved by adjusting various generating units' excitation systems continuously, discrete tap positions of on-load tap changers of transformers as well as switching of correct doses of inductors or capacitors. This is a mixed integer non-linear optimization problem. In this paper, the differential evolution (DE), a novel evolutionary computation technique which was originally designed for continuous problems is applied to solve this problem. DE appears to ally qualities of established computational intelligence (CI) techniques with a more striking computational performance, thus suggesting the possibility of having the potential for on line applications in the control center; comparison work with other techniques is presently conducted. The developed tool was demonstrated on the Nigerian power system grid for three case scenarios preset on the power world simulator which was linked with DE for power flow calculation (fitness check of solutions). The results achieved revealed that DE procured a significant reduction of real power losses while simultaneously keeping the voltage profiles within the acceptable limits.

关键词： Reactive power Power system simulation On load tap changers Transformers Inductors Capacitors Evolutionary computation Computational intelligence Computational modeling Load flow

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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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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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Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine Generators

Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine...

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2007 IEEE Power Engineering Society General Meeting (PES 2007), vol.10

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

A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. Concluding remarks are provided on how to choose an appropriate wind farm model for power system dynamic and transient studies.

关键词： Detailed model Equivalent model Fixed-speed wind turbine Squirrel-cage induction generator Wind farm

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Intelligent Local and Hierarchical Control of FACTS Devices

Intelligent Local and Hierarchical Control of FACTS Devices

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2007 IEEE Power Engineering Society Conference and Exposition in Africa (IEEE PES PowerAfrica 2007), part 1

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

This paper presents an overview of the applications of intelligent control techniques on local and hierarchical control of FACTS devices. These control techniques are superior to the conventional linear/nonlinear control schemes in the sense that they are independent of any mathematical model of the power system to be controlled. In addition, they do not depend on the operating conditions and the configuration of the system to which the FACTS device is connected. A Static Compensator (STATCOM) is used as the example in order to compare the performances of the proposed intelligent controllers with those of their linear counterparts. Nevertheless, the ideas put forth in this paper are applicable to other shunt or series FACTS devices as well. Two different control schemes are evaluated: a fuzzy logic based local controller and a neuro-fuzzy hierarchical controller for a STATCOM in a multimachine power system.

关键词： Nonlinear control systems Control systems Power system control Power systems Automatic voltage control Intelligent control Mathematical model Power system modeling Control system synthesis STATCOM

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TRACKING CONTROL IN THE PRESENCE OF NONLINEAR DYNAMIC FRICTIONAL EFFECTS: ROBOT EXTENSION

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Asian Journal of Control 2008年第3期1卷

作者： M. Feemster D.M. Dawson A. Behal W. Dixon Matthew Feemster received the B.S degree in Electrical Engineering from Clemson University Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962 in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no

In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.

关键词： Friction compensation nonlinear control

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