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Optimal control of class of non-linear plants using artificial immune systems: Application of the clonal selection algorithm

Optimal control of class of non-linear plants using artifici...

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2007 IEEE 22nd International Symposium on Intelligent Control, ISIC 2007

作者： Panimadai Ramaswamy, S.A. Venayagamoorthy, G.K. Balakrishnan, S.N. IEEE Department of Electrical and Computer Engineering University of Missouri Rolla MO 65409 United States Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO 65409 United States Department of Mechanical Aerospace and Engineering Mechanics University of Missouri Rolla MO 65409 United States

ISBN: (纸本)142440441X

The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear plants which are affine in control. The clonal selection algorithm is adapted for optimal control. A new mutation operator that operates on real values and one that aids in fast convergence is developed in this paper. AIS is used to obtain constant coefficient Kalman gain matrices. The validation and evaluation of the results thus obtained are carried out by comparing with standard and the widely used State Dependent Algebraic Riccati Equation (SDARE) method for the non-linear plants. In case of non-linear systems with hard state constraints, the SDARE formulation requires the use of mathematically involved expressions to incorporate these state constraints. However, the modified clonal selection algorithm developed in this paper has been used with hardly any changes to incorporate the hard state constraints and obtain the Kalman gain matrix. © 2007 IEEE.

关键词： Artificial intelligence

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Collaborative Routing Algorithm for Wireless Sensor Network Longevity

Collaborative Routing Algorithm for Wireless Sensor Network ...

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Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： Shishir Bashyal Ganesh Kumar Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

This study proposes a new parameter for evaluating longevity of wireless sensor networks after showing that the existing parameters do not properly evaluate the performance of algorithms in increasing longevity. This study also proposes an ant inspired Collaborative Routing Algorithm for Wireless Sensor Network Longevity (CRAWL) that has scalability and adaptability features required in most wireless sensor networks. Using the proposed longevity metrics and implementing the algorithm in simulations, it is shown that CRAWL is much more adaptive to non-uniform distribution of available energy in sensor networks. The performance of CRAWL is compared to that of a non-collaborative algorithm. Both algorithms perform equally well when the available energy distribution is uniform but when the distribution is non-uniform, CRAWL is found to have 20.2% longer network life. CRAWL performance degraded by just 10.1% when the available energy was unevenly distributed in the sensor network proving the algorithms adaptability.

关键词： Collaboration Routing Wireless sensor networks Scalability Energy resources Protocols Sensor phenomena and characterization Monitoring Intelligent sensors Energy consumption

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An Estimation of Distribution Improved Particle Swarm Optimization Algorithm

An Estimation of Distribution Improved Particle Swarm Optimi...

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Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： R. V. Kulkarni G. K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to optimization problems in areas including sensor networks.

关键词： Particle swarm optimization Ant colony optimization Electronic design automation and methodology Probability distribution Benchmark testing Optimization methods Equations Genetic mutations Space exploration real time systems

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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

作者： Wei, Qiao Harley, Ronald G. Venayagamoorthy, Ganesh K. IEEE School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States 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 65409-0249 United States

ISBN: (纸本)1424412986

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. © 2007 IEEE.

关键词： Power plants

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Self-healing control with multifunctional gate drive circuits for power converters

Self-healing control with multifunctional gate drive circuit...

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2007 IEEE Industry Applications Conference 42nd Annual Meeting, IAS

作者： Peng, Xiao Venayagamoorthy, Ganesh K. Corzine, Keith A. Woodley, Robert Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri-Rolla United States 21st Century Systems Inc. 199 E 4th St. Ft. Leonard Wood MO United States

ISBN: (纸本)1424403642

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its prefault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults. © 2007 IEEE.

关键词： Power converters

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Matching pursuit with frame-based psychoacoustic optimized WP-dictionary

Matching pursuit with frame-based psychoacoustic optimized W...

引用

Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2007

作者： Petrovsky, Alexey Rosa-Zurera, Manuel Alexandre Cortizo, Enrique Petrovsky, Alexander Computer Engineering Department Belarusian State University of Informatics and Radioelectronics 220013 Minsk Belarus Signal Theory and Communications Department University of Alcalá 28805 Madrid Spain Real-Time Systems Department Technical University Bialystok 15-351 Bialystok Poland

ISBN: (纸本)9781424415144

This paper presents the method of matching pursuit (MP) with frame based psychoacoustic optimized wavelet packet (WP) dictionary for selecting most relevant components to be used in compact representation transient part of signal. The wavelet dictionary for matching pursuit is composed of functions that are bounded by frame based psychoacoustic adaptive wavelet packet. Psychoacoustic motivated entropy based cost functions allow us to minimize perceptual relevance and adapt wavelet packet structure with reducing dictionary size. The proposed methodology for selecting most relevant components is based on maximising the matching between the auditory excitation scalograms associated with original and modelled signal correspondingly. This technique allows to significant reduce the number of MP atoms in compare with well known techniques based on damped sinusoids and over-complete WP-dictionary. © 2007 IEEE.

关键词： Wavelet analysis

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Software Technologies for Embedded and Ubiquitous systems: 5th IFIP WG 10.2 international workshop, SEUS 2007 santorini island, Greece, May 7-8, 2007 revised papers 5th

Software Technologies for Embedded and Ubiquitous Systems: 5...

引用

5th IFIP WG 10.2 International Workshop on Software Technologies for Embedded and Ubiquitous systems, SEUS 2007

作者： Obermaisser, Roman Nah, Yunmook Rammig, Franz J. Vienna University of Technology Real-Time Systems Group Treitlstr. 3/182-1 Wien Austria Dankook University Department of Electronics and Computer Engineering Hannam-dongYongsan-gu Seoul Korea Republic of University Paderborn Design of Parallel Systems Fürstenallee 11 Paderborn Germany

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Using micro-climate sensing to enhance RF localization in assisted living environments

Using micro-climate sensing to enhance RF localization in as...

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IEEE International Conference on systems, Man and Cybernetics

作者： Anthony Rowe Zane Starr Raj Rajkumar Real-Time and Multimedia Systems Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

In this paper, we propose micro-climate sensing as an effective means of enhancing conventional RF-based localization. Our system targets people-tracking applications in dynamic indoor environments, such as nursing homes, hospitals and office spaces that require simple deployment and where conventional RF-based tracking using signal strengths alone is very likely to suffer from time-varying signal attenuation and inevitable changes in the environment over time such as new furniture arrangements, people traffic, changing obstacle patterns etc. To help mitigate these effects, we use time-synchronized windows of sensor samples to dynamically associate a mobile node with its nearest beacon nodes. Comparisons and matches are always relative to the ambient attributes at the time of localization, and hence our technique automatically evolves with environmental changes. We consider this property of localization techniques to be a significant contribution and a necessary requirement for any long- lived localization system. In assisted-living environments, sensor networks likely already have basic sensors to collect contextual information about users and to monitor the environment. We propose using light, humidity, temperature and audio data samples over a short window of time to model the micro-climate of a beacon node. Using microclimate matching in conjunction with RF signal strength decreases the worst-case localization error significantly by a factor of more than 3 (from 25 m to 8 m) while making the system more resilient to environment changes. Microclimate data helps ensure at least room level location tracking even in buildings like hospitals with many rooms in close proximity.

关键词： Radio frequency Sensor phenomena and characterization Hospitals Biomedical monitoring Indoor environments Medical services Target tracking time varying systems Attenuation Humidity

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Autonomously Flying VTOL-Robots: Modeling and Control

Autonomously Flying VTOL-Robots: Modeling and Control

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Konstantin Kondak Markus Bernard Nicolas Meyer Gunter Hommel Real-Time Systems and Robotics Group Faculty of Electrical Engineering and Computer Science Technische Universitat Berlin Berlin Germany

In this paper an approach for control of autonomously flying robots with vertical take off and landing capabilities (VTOL) is presented. After reviewing that the motion description for different VTOL-robots is very similar, the general control scheme for VTOL-robots is presented. This scheme is based on linearisation and decoupling using inversion of the system model blocks. To compensate the model uncertainties and disturbances two additional parts are included into the controller: a reduced state observer based on a robot motion model as well as a disturbances observer and compensator for orientation control. The presented approach was applied to two different VTOL-robots: a helicopter and a quad-rotor. In real flight experiments it was verified that the presented general but simple controller provides sufficient performance for a wide range of practical applications.

关键词： Helicopters Robot sensing systems Gyroscopes Robotics and automation Automatic control Motion control Uncertainty Unmanned aerial vehicles Observers Delay estimation

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Identification of Induction Machines Stator Currents with Generalized Neurons

Identification of Induction Machines Stator Currents with Ge...

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2007 IEEE Power engineering Society Conference and Exposition in Africa (IEEE PES PowerAfrica 2007), part 2

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

A new approach to identify the nonlinear model of an induction machine using two generalized neurons (GNs) is presented in this paper. Compared to the multilayer perceptron feedforward neural network, a GN has simpler structure and lesser requirement in terms of memory storage which is makes it attractive for hardware implementation. This method shows that with less number of weights, GN is able to learn the dynamics of an induction machine. The proposed model is made by two coupled networks. A modified particle swarm optimization algorithm is designed to solve this distinctive GN training problem. A pseudo-random binary sequence signal injected to the induction machine operating at its rated value was chosen as the test input signal. For validation, the trained GN model is applied on the different operating conditions of the system.

关键词： Induction machines Stators Neurons Multilayer perceptrons Neural networks Multi-layer neural network Feedforward neural networks Neural network hardware Particle swarm optimization Algorithm design and analysis

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