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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Luka Kalinovcic Tamara Petrovic Stjepan Bogdan Vedran Bobanac Laboratory for Robotics and Intelligent Control Systems Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Laboratory for Renewable Energy Sources Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

In today's highly complex multi-AGV systems key research objective is finding a scheduling and routing policy that avoids deadlock while assuring that vehicle utilization is as high as possible. It is well known that finding such an optimal policy is a NP-hard task in general case. Therefore, big part of the research is oriented towards finding various suboptimal policies that can be applied to real world plants. In this paper we propose modified Banker's algorithm for scheduling in multi-AGV systems. A predetermined mission's path is executed in a way that some non-safe states are allowed in order to achieve better utilization of vehicles. A graph-based method of polynomial complexity for verification of these states is given. Algorithm is tested on a layout of a real plant for packing and warehousing palettes. Results shown at the end of the paper demonstrate advantages of the proposed method compared with other methods based on Banker's algorithm.

关键词： Vehicles System recovery Layout Resource management Job shop scheduling Workstations

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Agent self-assessment: Determining policy quality without execution

Agent self-assessment: Determining policy quality without ex...

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Alexander Hans Siegmund Duell Steffen Udluft Neuroinformatics and Cognitive Robotics Laboratory Ilmenau University of Technology Ilmenau Germany Machine Learning Group Berlin Institute of Technology Berlin Germany Intelligent Systems and Control Siemens AG Munich Germany

With the development of data-efficient reinforcement learning (RL) methods, a promising data-driven solution for optimal control of complex technical systems has become available. For the application of RL to a technical system, it is usually required to evaluate a policy before actually applying it to ensure it operates the system safely and within required performance bounds. In benchmark applications one can use the system dynamics directly to measure the policy quality. In real applications, however, this might be too expensive or even impossible. Being unable to evaluate the policy without using the actual system hinders the application of RL to autonomous controllers. As a first step toward agent self-assessment, we deal with discrete MDPs in this paper. We propose to use the value function along with its uncertainty to assess a policy's quality and show that, when dealing with an MDP estimated from observations, the value function itself can be misleading. We address this problem by determining the value function's uncertainty through uncertainty propagation and evaluate the approach using a number of benchmark applications.

关键词： Uncertainty Equations Markov processes Benchmark testing Approximation algorithms Machine learning Histograms

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Enhancing student learning: On-line interactive laboratory for modelling of real world control system applications

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IFAC Proceedings Volumes 2011年第1期44卷 7268-7273页

作者： Joshué Pérez Sebastián Dormido Ljubo Vlacic Centre of Automation and Robotics (CAR) University Polytechnic of Madrid (UPM) – Spanish National Research Council (CSIC) Madrid Spain Dep. Informática y Automática Escuela Técnica Superior de Ingeniería Informática Universidad Nacional de Educación a Distancia Madrid Spain Intelligent Control Systems Laboratory Griffith University Brisbane Australia

Abstract Teaching an introductory course on control systems to undergraduate students often seeks elaborations on real engineering world control system applications to assist students in grasping theoretical concepts. In this paper, the newly developed animated and interactive control systems tutorials are presented. The paper shows that this teaching approach helps students in bridging the gap between the classical control techniques and the real world applications. The course evaluations undertaken since the time of the inclusion of the animated tutorials into the teaching process clearly show the learning improvement gained, reflected in increased average scores, and reduced course fail grade.

关键词： Interactive control system tutorials Interactive teaching tools Animation Distance Education

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Light-weight mobile robot for hydrodynamic treatment of concrete and metal surfaces

Light-weight mobile robot for hydrodynamic treatment of conc...

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International Conference on Applied robotics for the Power Industry (CARPI)

作者： Zdenko Kovacic Borislav Balac Stjepan Flegaric Kristijan Brkic Matko Orsag LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of electrical Engineering and Computing University of Zagreb Zagreb Croatia Inteco d o o Zagreb Croatia

The paper presents a modular design of a lightweight mobile robot for hydrodynamic treatment of concrete and metal surfaces. The robot is composed of three fully separable modules: an under-carriage with two tracks, an electric cabinet containing power electronics, communication and control, and a robot arm with various water jet tools. Modularity and smaller robot weight allows easy transportation, operation in ordinary construction conditions and maneuvering in very confined spaces. The on-board PLC controls the following robot axes: two robot tracks, a beam, a rotor tool, lance swing and pitch angles, and tool-to-surface distance deviation. Ultrasound sensors mounted on the robot allow automatic adjustment of a tool towards a treated surface. Experimental results obtained in real exploitation conditions (during a bridge repair) have confirmed all advantages of the described robot design.

关键词： Power industry Service robots Conferences

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Ensembles of Neural Networks for Robust Reinforcement Learning

Ensembles of Neural Networks for Robust Reinforcement Learni...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Alexander Hans Steffen Udluft Neuroinformatics and Cognitive Robotics Laboratory Ilmenau University of Technology Ilmenau Germany Intelligent Systems and Control Corporate Technology Siemens AG Germany

Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their training and the validation of final policies can be cumbersome as neural networks can suffer from problems like local minima or over fitting. When using iterative methods, such as neural fitted Q-iteration, the problem becomes even more pronounced since the network has to be trained multiple times and the training process in one iteration builds on the network trained in the previous iteration. Therefore errors can accumulate. In this paper we propose to use ensembles of networks to make the learning process more robust and produce near-optimal policies more reliably. We name various ways of combining single networks to an ensemble that results in a final ensemble policy and show the potential of the approach using a benchmark application. Our experiments indicate that majority voting is superior to Q-averaging and using heterogeneous ensembles (different network topologies) is advisable.

关键词： Training Function approximation Artificial neural networks Network topology Approximation algorithms Neurons

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Editorial Special issue on approximate dynamic programming and reinforcement learning

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控制理论与应用（英文版） 2011年第3期 309-309页

作者： Silvia Ferrari Jagannathan Sarangapani Frank L. Lewis Laboratory for Intelligent Systems and Control(LISC)Department of Mechanical Engineering & Materials Science Box 90300 Duke University Durham NC 27708-0005 Department of Electrical & Computer Engineering University of Missouri-Rolla MO 65401 U.S.A. Automation and Robotics Research Institute The University of Texas at Arlington 7300 Jack Newell Blvd. S Ft. Worth Texas 76118-7115 U.S.A.

We are extremely pleased to present this special issue of the Journal of control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over *** optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.

关键词： reinforcement learning dynamic programming optimal control effective approach prior knowledge control Theory real-time control law problems special search future ADP basis

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Determination of circular waits in multiple-reentrant flowlines based on machine-job incidence matrix 10

Determination of circular waits in multiple-reentrant flowli...

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2009 10th European control Conference, ECC 2009

作者： Petrovic, Tamara Bogdan, Stjepan Sindicic, Ivica Laboratory for Robotics and Intelligent Control Systems Department of Control and Computer Engineering University of Zagreb Zagreb Croatia Exor D.o.o Bani 72 Zagreb10000 Croatia

ISBN: (纸本)9783952417393

As the first step in resolving stability of a manufacturing system in the sense of deadlock, calculation of circular waits might involve time and memory consuming calculations. In this paper we propose an efficient method for determination of circular waits in multiple-reentrant flowline class (MRF) of manufacturing systems. We introduce machine-job incidence (MJI) matrix that can be obtained from Steward sequencing matrix and Kusiak machine-part incidence matrix. The method uses index vector and MJI matrix in order to allocate circular wait auxiliary vector. Resources involved in the circular wait are directly computed from the auxiliary vector. Although efficiency of the proposed method has been demonstrated on examples involving single- and multi- part type manufacturing workcells, the method can be used for other discrete event systems as well, as long as the system under study belongs to MRF class. © 2009 EUCA.

关键词： Manufacture

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control system for reactor vessel inspection manipulator

Control system for reactor vessel inspection manipulator

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IEEE Conference on control Technology and Applications (CCTA)

作者： Alan Mutka Ivica Draganjac Zdenko Kovacic Zeljko Postruzin Ranko Munk Faculty of EE&C Department of Control and Computer Engineering LARICS-Laboratory of Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia Organization of Technology Development and Application HRID Limited Zagreb Croatia

In this paper a system for control and 3D visualization of a manipulator for weld inspection of nuclear reactor vessels is described. Based on client-server TCP/IP software architecture, the presented control system enables an operator to perform the entire inspection procedure remotely over a network, avoiding exposure to dangerous radiation which is commonly present in nuclear reactor environments. The developed graphical user interface provides all necessary tools needed for planning robot scan trajectories, their verification on a virtual 3D model and execution on a remote robot. In addition, the weld inspection process can be observed in parallel on a virtual robot and reactor vessel model and on live video streams captured by two special cameras mounted on the robot.

关键词： control systems Inductors Inspection Welding Parallel robots Visualization TCPIP Software architecture Graphical user interfaces Trajectory

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Matrix-Based Approach to Sequence analysis in Multiple Reentrant Flowlines

Matrix-Based Approach to Sequence analysis in Multiple Reent...

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2008 American control Conference (ACC), vol.3

作者： Tamara Petrovic Stjepan Bogdan LARICS-Laboratory for Advanced Robotics and Intelligent Control Systems Faculty of Electrical Engeneering and Computing University of Zagreb Croatia

This paper presents a method for extension of matrix model of manufacturing system in order to provide an efficient tool for analysis of systems with various dispatching sequences of shared resources. Proposed method is used for transformation of system matrices in linear max-plus model. Once the linear model is determined sequence feasibility can be checked. Furthermore, the method provides a straightforward procedure for production cycle calculation and resource utilisation. Efficiency of presented technique is demonstrated on a manufacturing system example at the end of the paper.

关键词： Manufacturing systems Dispatching Resource management Production Flexible manufacturing systems Algebra Laboratories intelligent robots intelligent control Computer aided manufacturing

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Fuzzy logic navigation in multi agent systems

Fuzzy logic navigation in multi agent systems

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IEEE International Symposium on intelligent control (ISIC)

作者： S. Bogdan I. Rigo D. Miklic LARICS-Laboratory for Advanced Robotics and Intelligent Control Systems Faculty of EE&C University of Zagreb Croatia

ISBN: (纸本)9781424422241

In this paper we present a methodology for decision making in multi agent system comprised of agents driven by repulsive force and attracting force. Navigation functions are expressed as a set of fuzzy rules obtained by fuzzy Lyapunov stability criteria, thus ensuring stability of the overall system. The goal of the proposed methodology is to create desired formations by moving agents from their initial positions to formation targets, while in the same time avoiding collisions. The destination targets are dynamically permutated as long as the required formation is achieved.

关键词： intelligent control control systems USA Councils

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