Development of active icosahedron and its application to virtual clay modeling

We have developed an active link mechanism for physical man-machine interaction. We report an active icosahedron consisting of intelligent cylinders and its application to virtual clay modeling. Intelligent pneumatic cylinders are newly developed to realize active link mechanisms. This cylinder aims at a novel cylinder in which various sensors and control devices are built. Active link mechanisms are highly integrated and enhanced by intelligent cylinders. A control system is built for the active icosahedron. In the control system, a key element is a control program implementing drawing of a virtual model on display and controlling of active links. Virtual clays are deformed by the program based on the apex positions converted from cylinder lengths. The active icosahedron realized dynamic interaction with virtual objects in PC, showing the potential of the devices as a haptic interface.</p

A system of intelligent algorithms for a module of onboard equipment of mobile vehicles

The area of intelligent robotics is moving from the single robot control problem to that of controlling multiple robots operating together and even collaborating in dynamic and unstructured intelligent environments. In such conditions, an intelligent robot control system is only part of general intelligent system. In this paper, we consider a model of such system. © 2013 Anna Gorbenko

Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit

The concept of an intelligent control system for a complex nonlinear biomechanical system of an extension cableless robotic unicycle discussed. A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems applied. The results of stochastic simulation of a fuzzy intelligent control system for various types of external / internal excitations for a dynamic, globally unstable control object - extension cableless robotic unicycle based on Soft Computing (Computational Intelligence Toolkit - SCOptKBTM) technology presented. A new approach to design an intelligent control system based on the principle of the minimum entropy production (minimum of useful resource losses) determination in the movement of the control object and the control system is developed. This determination as a fitness function in the genetic algorithm is used to achieve robust control of a robotic unicycle. An algorithm for entropy production computing and representation of their relationship with the Lyapunov function (a measure of stochastic robust stability) described

Intelligent coordination steering control of automated guided vehicle

In this paper, based on the neural network, fuzzy control and bang-bang control, an intelligent coordination control strategy for automated guided vehicle (AGV) steering system is presented. The dynamic steering model of distance error and orientation angle error for AGV is expressed. With least square method of system identification, the model of AGV is identified. Because a toy type of AGV is employed, its structure is simple, but AGV model parameters are variable according to the operating conditions and environment. In order to improve the dynamic performances of AGV, the intelligent coordinated control strategy is used to design the AGV controller in the AGV steering control system. Simulation and experimental results show the effectiveness of the proposed control strategy. © 2011 IEEE

An Intelligent Knowledge Management System from a Semantic Perspective

Abstract. Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

Design and Testing Neuro Networks Control System for Direct Current Machine

The paper presents an adaptive intelligent control method to overcome effects of some indeterminate and undealt factors that a DC. drive is suffered. In the speed loop, we use a three-layer neural networks through a backpropagation (BP) algorithm out of line learning to realize the fuzzy-control tactics. We use unit neuron through Hebb algorithm on-line dynamic learning to realize adaptive mechanism. The simulation is based on a MATLAB neural networks toolbox with simulink. The results of the simulation show that adaptive intelligent control method enables the system to have good dynamic and stability performance. The proposed method develops the use of simulink in the field of electrical drive of adaptive intelligent control

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

A Radio-fingerprinting-based Vehicle Classification System for Intelligent Traffic Control in Smart Cities

The measurement and provision of precise and upto-date traffic-related key performance indicators is a key element and crucial factor for intelligent traffic controls systems in upcoming smart cities. The street network is considered as a highly-dynamic Cyber Physical System (CPS) where measured information forms the foundation for dynamic control methods aiming to optimize the overall system state. Apart from global system parameters like traffic flow and density, specific data such as velocity of individual vehicles as well as vehicle type information can be leveraged for highly sophisticated traffic control methods like dynamic type-specific lane assignments. Consequently, solutions for acquiring these kinds of information are required and have to comply with strict requirements ranging from accuracy over cost-efficiency to privacy preservation. In this paper, we present a system for classifying vehicles based on their radio-fingerprint. In contrast to other approaches, the proposed system is able to provide real-time capable and precise vehicle classification as well as cost-efficient installation and maintenance, privacy preservation and weather independence. The system performance in terms of accuracy and resource-efficiency is evaluated in the field using comprehensive measurements. Using a machine learning based approach, the resulting success ratio for classifying cars and trucks is above 99%

A modular and interactive OLED-based lighting system

The concept of a flexible, large-area, organic light emitting diode (OLED)-based lighting system with a modular structure and built-in intelligent light management is introduced. Such a flexible, thin, portable lighting system with discreetly integrated electronics is important in order to allow the implementation of the lighting system into a variety of places, such as cars and temporary expedition areas. A modular construction of an OLED lighting panel makes it possible to control each OLED cell individually. This not only enables us to counteract aging or degradation effects in the OLED cells but it also allows individual OLED module brightness control to support human or ambient interaction based on integrated or centralized sensors. Moreover, integrating the driving electronics in the backplane of an OLED module improves the energy efficiency of operating large OLED panels. The thin, modular construction and individual, dynamic control are successfully demonstrated