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检索条件"主题词=Control Engineering Computing"

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Stability Improvement of Power Networks using Cluster based Dynamic Excitation of AVR

Stability Improvement of Power Networks using Cluster based ...

引用

IEEE Annual Ubiquitous computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Brook W. Abegaz Loyola University Chicago Chicago IL USA

ISBN: (纸本)9781728138862

The dynamic stability of power systems consisting of multiple machines is affected by the excitation of each machine, the system configuration and the loading conditions. In this paper, a method that could improve the dynamic stability of power networks in the presence of internal and external disturbances is presented. Automatic voltage regulator (AVR) based clustering and dynamic excitation of machines is proposed. Distributed perturbations are used to evaluate the stability of an experimental New England 10-machine, 39-bus test system. From the results, it was seen that the proposed clustering-based excitation algorithm could uniquely improve the stability conditions of the perturbed New effectively power system by around 10%, which could not be achieved using other methods.

关键词： control engineering computing pattern clustering power system control power system stability voltage control voltage regulators Power system stability control engineering computing Power grids Voltage regulators Power system control automatic voltage regulator Voltage regulation Cluster Analysis stability improvement Dynamic stability power system dynamic stability Excitation machine power systems

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Lyapunov-based adaptive control of MIMO systems

Lyapunov-based adaptive control of MIMO systems

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American control Conference (ACC)

作者： Liu Hsu R. Costa A.K. Imai P. Kokotovic Department of Electrical Engineering COPPE/UFRJ Rio de Janeiro Brazil Â‡ Center for Control Engineering and Computation University of California Santa Barbara CA

The design of model-reference adaptive control (MRAC) for MIMO linear systems has not yet been achieved, in spite of significant efforts, the completeness and simplicity of its SISO counterpart. One of the main obstacles has been the generalization of the SISO assumption that the sign of the high-frequency gain is known. Here we overcome this obstacle and present a MIMO analog to the well known Lyapunov-based MRAC SISO design. Our algorithm makes use of a new control parametrization derived from a factorization of the high-frequency gain matrix K/sub p/=SDU, where S is symmetric positive definite, D is diagonal, and U is unity upper triangular. Only the signs of the entries of D or, equivalently, the signs of the leading principal minors of K/sub p/, are assumed to be known.

关键词： Adaptive control MIMO Linear systems Frequency Transmission line matrix methods Symmetric matrices Visual servoing Upper bound control engineering control engineering computing

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Fuzzy control for Platooning Systems Based on V2V Communication

Fuzzy Control for Platooning Systems Based on V2V Communicat...

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International Conference on computing, Electronics & Communications engineering (iCCECE)

作者： Handong Li Rajesh Tiwari Volker. Pickert Satnam. Dlay School of Engineering Newcastle University Newcastle Upon Tyne UK Nottingham Scientific Ltd. UK Nottingham UK

ISBN: (纸本)9781538649053;9781538649046

In this paper, we developed an innovative approach using adaptive PID (Proportion, integral and derivation) controller using fuzzy logic theory to keep variable time-gap between dynamic cars, particularly for platooning system. Our study shows that robustness in maintaining gap between the dynamic cars, despite the specific vehicle model. In order to demonstrate robustness, in our study for the platooning *** requires a set of information needed to be exchange using V2V communication protocol. However, the set of information required vehicle state dynamic information from the vehicle in front of itself. The simulation results presented in this paper show a significant improvement in keeping time-gap variable between the cars to have a safe and efficient flow of the platoonina system.

关键词： adaptive control control engineering computing fuzzy control fuzzy logic protocols road safety road vehicles three-term control traffic engineering computing vehicular ad hoc networks Three term control systems V2V control engineering computing Fuzzy control road vehicles Fuzzy logic Road safety Car following adaptive control protocols engineering computing Cars Land transportation vehicle

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Multi-agent control system for the exploitation of vehicle to grid in active LV networks

Multi-agent control system for the exploitation of vehicle t...

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CIRED Workshop 2016

作者： Susanna Mocci Nicola Natale Fabrizio Pilo Simona Ruggeri Universita degli Studi di Cagliari Cagliari Sardegna IT

ISBN: (纸本)9781510834675

Worldwide considerable resources in terms of R&D have commissioned in the field of electrical mobility. Due to the significant dissemination of Electric Vehicles (EVs) predicted in the near future, the concept of vehicle-to-grid (V2G) will be practically achievable, to improve the integration of renewable energy into distribution networks and leads to economic and environment benefits, supporting the grid operation, reducing substation transformers and line overloading to defer or even avoid investments. In the paper, an intelligent and decentralized Multi Agent System for managing EV charging/discharging in LV distribution networks is proposed.

关键词： power engineering computing control engineering computing electric vehicles multi-agent systems power distribution control

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MPC-trained ANFIS for control of MicroCSP Integrated into a Building HVAC System

MPC-trained ANFIS for Control of MicroCSP Integrated into a ...

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American control Conference

作者： Mohamed Toub Mahdi Shahbakhti Rush D. Robinett Ghassane Aniba Mohammadia School of Engineering Mohammed V University of Rabat Rabat Morocco Michigan Technological University Houghton MI USA Mohammadia School of Engineering Mohammed V University of Rabat Ra

ISBN: (纸本)9781538679012;9781538679265

This paper presents the design of an easily implementable rule-based controller that can minimize the electrical energy consumption of a building heating, ventilation, and air-conditioning (HVAC) system integrated with a microscale concentrated solar power (MicroCSP) system. A model predictive control (MPC) scheme is developed to optimize Mi-croCSP electrical and thermal energy flows for HVAC use in a building. Despite its attractiveness regarding energy savings and thermal comfort satisfaction, MPC requires high computational resources and can not be easily implemented on the common low-cost HVAC controllers available in the market. To cope with these issues, two MPC-trained adaptive neuro-fuzzy inference system (ANFIS) models are designed to control the building HVAC with MicroCSP. Simulation results exploiting real operation data from an office building at Michigan Technological University and our newly purchased MicroCSP are presented. It is shown that the resulting controller can reproduce the MPC reasoning and performance while being simpler and much more computationally efficient.

关键词： building management systems control engineering computing energy conservation fuzzy neural nets fuzzy reasoning HVAC neurocontrollers power engineering computing predictive control space heating heating ventilation and air conditioning Fuzzy neural networks control engineering computing Building management systems Power engineering computing Neurocontrollers Predictive control fuzzy reasoning Space heating Energy conservation office buildings Buildings

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Beyond the Smart Home

Beyond the Smart Home

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International Conference on Hybrid Information Technology, ICHIT

作者： Tatsuya Yamazaki Knowledge Creating Communication Research Center National Institute of Information and Communications Technology Japan

Due to progress in wired and wireless home networking, sensor networks, networked appliances, mechanical and control engineering, and computers, we can build smart homes, and many smart home projects are currently proceeding throughout the world. However, we have to be careful not to repeat the same mistake that was made with home automation technologies that were booming in the 1970s. That is, [total?] automation should not be a goal of smart home technologies. I believe the following points are important in construction of smart homes from users' viewpoints: development of interface technologies between humans and systems for detection of human intensions, feelings, and situations; improvement of system knowledge; and extension of human activity support outside homes to the scopes of communities, towns, and cities.

关键词： Smart homes Humans Wireless sensor networks Home automation Intelligent sensors Mechanical sensors Home appliances control engineering control engineering computing Computer networks

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Geographical Cells: Location-Aware Adaptive Routing Scheme for Ad-Hoc Networks

Geographical Cells: Location-Aware Adaptive Routing Scheme f...

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Eurocon

作者： Michal Kudelski Andrzej Pacut Institute of Control and Computation Engineering Warsaw University of Technology Warsaw Poland

We introduce an novel approach to information management in ad-hoc networks, based on geographical cells concept. Geographical cells are used to comprise the information within the geographical location. We apply this approach to solve the problem of routing in ad-hoc networks for various mobility models. We show that the geographical cells approach may improve the overall performance of the underlying routing mechanism.

关键词： Routing Ad hoc networks Information management Clustering algorithms Computer networks Mobile communication Programmable control Adaptive control control engineering computing Adaptive systems

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SPEED controlLING & TRAFFIC MANAGEMENT SYSTEM (SCTMS)

SPEED CONTROLLING & TRAFFIC MANAGEMENT SYSTEM (SCTMS)

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IEEE Annual Ubiquitous computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Aneesh Kar Soujanya Syamal Suvraneel Chatterjee Antarika Basu Himadri Nath Saha Srijata Choudhuri Institute of Engineering & Management (I.E.M) KOLKATA INDIA Institute of Engineering & Management(I.E.M.) KOLKATA INDIA

ISBN: (纸本)9781728138862

This paper is based on Electronic Vehicle System, like any other electric vehicle, with certain additional, new features which will take electronic vehicles to a whole new level. Speed management, thereby contributing to traffic management has always been a very big challenge to us. The safety and the smooth flow of traffic is very much essential. To overcome these huddles, it is necessary to device a smart vehicle system, which will be responsible to regulate the speed of the vehicle and manage the traffic. Firstly, to control the speed, we need to device a three condition layer, which is based on Data Analytics, Machine Learning, Deep Learning and IOT. This three-layered System will get the maximum speed of the car, beyond which the driver will be unable to drive. Obtaining the maximum speed limit will depend on factors like the prescribed maximum speed limit of the particular road, the car is running on, the present traffic density of the road and the traffic situation as per the nearby traffic pole, the position of the other cars with respect to the concerned car. All these major factors will attribute to obtaining a safe maximum speed limit, as the three-layered system will work simultaneously, enabling the driver to drive safely within this limit. Since speed management can be reached, this will attribute to the management of the traffic. The knowledge of IOT is necessary, which will connect the car and the nearby traffic pole. Once they are connected, the car will receive signals and updates, regarding the traffic situation and based on the color of the signal the car will adjust it's speed or stop, accordingly. These are the major aspects of this proposed new vehicle system. Thus, the System can prove to be very much beneficial.

关键词： automobiles control engineering computing data analysis electric vehicles Internet of Things learning (artificial intelligence) road safety road vehicles traffic engineering computing velocity control Cars Internet of things control engineering computing Velocity control Electric vehicles road vehicles Traffic maximum speed Road safety Automobiles Speed limit Carina Data analysis engineering computing vehicle

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Neural modules: networks with constrained architectures for nonlinear function identification

Neural modules: networks with constrained architectures for ...

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International Workshop on Neural Networks for Identification, control, Robotics, and Signal/Image Processing

作者： B. Morcego J.M. Fuertes G. Cembrano Automatic Control and Computer Engineering Department Universitat Politecnica de Catalunya Barcelona Spain Institute of Cybemetics Universitat Politecnica de Catalunya Barcelona Spain

The aim of this work is the design of a class of neural networks for nonlinear function identification: the so-called neural modules. A neural module is a neural network with an internal structure specially designed to be able to learn and mimic the behaviour of a certain class of dynamic systems. Neural networks are abstract models well suited for approximating nonlinear functions. The training cost and the structural complexity of neural networks can be drastically reduced if a-priori knowledge of the function to be learned is internally incorporated in the form of structural constraints. The resulting neural network has less parameters than a conventional one, much faster learning convergence and it can provide meaningful information about the learned nonlinear function. This paper describes the design of a useful set of neural modules for system identification and gives general guidelines for the design of neural modules. The resulting networks are evaluated and their use on general systems identification is pointed out.

关键词： Artificial neural networks Neural networks System identification Guidelines control systems Nonlinear systems Network topology Computer architecture Automatic control control engineering computing

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An Interactive Lane Change Decision Making Model With Deep Reinforcement Learning

An Interactive Lane Change Decision Making Model With Deep R...

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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Shenghao Jiang Jiying Chen Macheng Shen School of Engineering and Applied Sciences Harvard University Cambridge USA College of New Energy China University of Petroleum Qingdao China Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge USA

By considering lane change maneuver as primarily a Partial Observed Markov Decision Process (POMDP) and motion planning problem, this paper presents an interactive model with a Recurrent Neural Network (RNN) approach to determine the adversarial or cooperative intention probability of following vehicle in target lane. To make proper and efficient lane change decision, Deep Q-value network (DQN) is applied to solve POMDP with expected global maximum reward. Then quintic polynomials-based motion planning algorithm is used to obtain both optimal lateral and longitudinal trajectory for autonomous vehicle to pursuit. Experimental results demonstrate the capability of the proposed model to execute lane change maneuver with comfortable and safety reference trajectory at an appropriate time instance and traffic gap in various highway traffic scenarios.

关键词： control engineering computing decision making decision theory learning (artificial intelligence) Markov processes optimal control path planning polynomials probability recurrent neural nets road traffic control road vehicles traffic engineering computing

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