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arXiv 2019年

作者： Tyburec, Marek Zeman, Jan Kružík, Martin Henrion, Didier Departement of Mechanics Faculty of Civil Engineering Czech Technical University in Prague Thákurova 7 Prague 6166 29 Czech Republic Departement of Physics Faculty of Civil Engineering Czech Technical University in Prague Thákurova 7 Prague 6166 29 Czech Republic Institute of Information Theory and Automation Czech Academy of Sciences Pod vodárenskou věží 4 Prague 8182 08 Czech Republic LAAS-CNRS University of Toulouse 7 Avenue du Colonel Roche Toulouse31400 France Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Karlovo náměstí 13 Prague 2121 35 Czech Republic

Optimization of frame structures is formulated as a non-convex optimization problem, which is currently solved to local optimality. In this contribution, we investigate four optimization approaches: (i) general non-linear optimization, (ii) optimality criteria method, (iii) non-linear semidefinite programming, and (iv) polynomial optimization. We show that polynomial optimization solves the frame structure optimization to global optimality by building the (moment-sums-of-squares) hierarchy of convex linear semidefinite programming problems, and it also provides guaranteed lower and upper bounds on optimal design. Finally, we solve three sample optimization problems and conclude that the local optimization approaches may indeed converge to local optima, without any solution quality measure, or even to infeasible points. These issues are readily overcome by using polynomial optimization, which exhibits a finite convergence, at the prize of higher computational demands. Copyright © 2019, The Authors. All rights reserved.

关键词： Shape optimization

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Saturated Continuous Twisting Algorithm

Saturated Continuous Twisting Algorithm

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International Workshop on Variable Structure Systems, VSS

作者： M. A. Golkani L. M. Fridman S. Koch M. Reichhartinger M. Horn Faculty of Electrical and Information Engineering Graz University of Technology Graz Austria Department of Control Engineering and Robotics National Autonomous University of Mexico México D.F. Mexico Christian Doppler Laboratory for Model Based Control of Complex Test Bed Systems Graz University of Technology Graz Austria

In this paper, a second-order system affected by perturbations is considered. A feedback control law adopting the continuous twisting algorithm is designed such that a saturated and continuous control signal is introduced to the system. In the case that a state variable is not measurable, estimate information obtained through a super-twisting observer is incorporated into the design. For the closed-loops (with and without observer), global finite-time stability properties are established. The feasibility and effectiveness of the strategy is shown employing numerical simulations.

关键词： Stability analysis Lyapunov methods Observers Perturbation methods Heuristic algorithms Actuators Feedback control

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Development of a Tetris Playing Robot controlled by KNR

Development of a Tetris Playing Robot Controlled by KNR

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IEEE International Conference on Mechatronics and Automation

作者： Ming Wang Yanlu Zhang Huifang Dong Xu Li Junzhi Yu Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system.

关键词： Mobile robots Cameras Robot sensing systems Image color analysis Servomotors Robot kinematics

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Parameter adaptation of simplified switched reluctance motor model using Newton and Gauss-Newton signal fitting methods

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COMPEL 2017年第3期36卷 602-618页

作者： Fabianski, Bogdan bogdan.fabianski@put.poznan.pl Zawirski, Krzysztof krzysztof.zawirski@put.poznan.pl Faculty of Electrical Engineering Institute of Control and Information Engineering Politechnika Poznanska Poznan Poland

Purpose The paper is concerned about parameter adaptation of a novel, simplified and nonlinear switched reluctance motor (SRM) model. The purpose of the presented on-line procedure is to give an opportunity to set the model parameters’ values to obtain a relatively good convergence with the real control object. This is important when a reference model is used for control (e.g. optimal) or object state classification (e.g. fault detection) purposes. The more convergent the real object model is, the better operation quality may be ***/methodology/approach In the paper, a 12/8 pole’s SRM as a control object is analyzed. The model equations were verified experimentally by comparing phase current model estimations with reference (measured) ones at different operational points. Differential equations of motor winding currents were chosen as an approximation function in the fitting (parameter adaptation) process using the Newton and Gauss–Newton methods. The structure of the adaptation system is presented along with the implementation in simulation *** It was confirmed in the simulation tests that Newton and Gauss–Newton methods of nonlinear model parameters’ adaptation may be used for the SRM. The introduced fitting structure is well suited for implementation in real-time, embedded systems. The proposed approximation function could be used in process as an expansion to Jacobian and Hessian matrices. The χ2 (chi2) coefficient (commonly used to measure the quality of the signal fitting) reduced to a low value during the adaptation process. Another introduced quality coefficient shows that the Newton method is slightly better in scope of the entire adaptation process time; however, it needs more computational *** limitations/implications The proposed structure and approximation function formula in the parameters’ adaptation system is appropriate for sinusoidal distribution of the motor phase inductance value along the rotor angle posit

关键词： control system Electric drive Modeling Newton method Nonlinear approximation Switched reluctance motor

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Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems

arXiv

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arXiv 2018年

作者： Han, Zhonghua Tian, Xutian Dong, Xiaoting Xie, Fanyi Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China Department of Digital Factory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning China Faculty of Electrical Engineering Sichuan College of Architectural Technology Deyang Sichuan China

In order to solve Re-entrant Hybrid Flowshop (RHFS) scheduling problems and establish simulations and processing models, this paper uses Wolf Pack Algorithm (WPA) as global optimization. For local assignment, it takes minimum remaining time rule. Scouting behaviors of wolf are changed in former optimization by means of levy flight, extending searching ranges and increasing rapidity of convergence. When it comes to local extremum of WPA, dynamic regenerating individuals with high similarity adds diversity. Hanming distance is used to judge individual similarity for increased quality of individuals, enhanced search performance of the algorithm in solution space and promoted evolutionary vitality.A painting workshop in a bus manufacture enterprise owns typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focus on resolving this problem with LDWPA (Dynamic wolf pack algorithm based on Levy Flight). Results show that LDWPA can solve re-entrant hybrid flowshop scheduling problems effectively. Copyright © 2018, The Authors. All rights reserved.

关键词： Global optimization

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Sensorless nonlinear control of fed-batch Escherichia coli cultivation bioprocess using the state-dependent approach 12th

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12th Portuguese Conference on Automatic control, controlO 2016

作者： Iratni, Abdelhamid Araújo, Rui Rastegar, Saeid Mostefai, Mohammed Faculty of Science and Technology Electrical Engineering Department University of Bordj Bou Arreridj El Anasser Algeria Department of Electrical and Computer Engineering Institute for Systems and Robotics University of Coimbra Coimbra Portugal Automatic Control Laboratory of Setif Electrical Engineering Department Faculty of Technology University of Setif1 Sétif Algeria

ISBN: (纸本)9783319436708

The cultivation of Escherichia coli bacteria is widely used by geneticists and biopharmaceuticals to produce medicines and vaccines. In such industries, Bioprocesses are known by their harsh environment and very expensive physical sensors. This paper deals with nonlinear estimation and control of fed-batch Escherichia coli bioprocess. Enhancing the process performance and maximizing its efficiency by optimizing the control of Escherichia coli cultures depends on the availability of appropriate online sensors for the main culture components. In this study, an innovative method for nonlinear estimation and control of bioprocesses is designed and assessed. The new algorithm for control and estimation of Escherichia coli bioprocess states, based on the State-Dependent Riccati Equation technique, is validated by numerical simulation. The results obtained clearly demonstrate the effectiveness of the proposed technique for Biosystems in measuring, monitoring, and control of their natural nonlinear dynamics. © Springer International Publishing Switzerland 2017.

关键词： Extended Kalman filters

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Dynamically weighted ensemble-based prediction system for adaptively modeling driver reaction time

arXiv

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arXiv 2018年

作者： Chuang, Chun-Hsiang Cao, Zehong Chen, Po-Tsang Huang, Chih-Sheng Pal, Nikhil R. Lin, Chin-Teng Department of Computer Science and Engineering National Taiwan Ocean University Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Australia Discipline of ICT School of Technology Environments and Design University of Tasmania TAS Australia Brain Research Center National Chiao Tung University Taiwan Institute of Electrical Control Engineering Indian Statistical Institute India Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia

Motor vehicle crashes are the leading cause of fatalities worldwide. Most of these accidents are caused by human mistakes and behavioral lapses, especially when the driver is drowsy, fatigued, or inattentive. Clearly, predicting a driver's cognitive state, or more specifically, modeling a driver's reaction time (RT) in response to the appearance of a potential hazard warrants urgent research. In the last two decades, the electric field that is generated by the activities in the brain, monitored by an electroencephalogram (EEG), has been proven to be a robust physiological indicator of human behavior. However, mapping the human brain can be extremely challenging, especially owing to the variability in human beings over time, both within and among individuals. Factors such as fatigue, inattention and stress can induce homeostatic changes in the brain, which affect the observed relationship between brain dynamics and behavioral performance, and thus make the existing systems for predicting RT difficult to generalize. To solve this problem, an ensemblebased weighted prediction system is presented herein. This system comprises a set of prediction sub-models that are individually trained using groups of data with similar EEG-RT relationships. To obtain a final prediction, the prediction outcomes of the submodels are then multiplied by weights that are derived from the EEG alpha coherences of 10 channels plus theta band powers of 30 channels, whose changes were found to be indicators of variations in the EEG-RT relationship. The results thus obtained reveal that the proposed system with a time-varying adaptive weighting mechanism significantly outperforms the conventional system in modeling a driver's RT. The adaptive design of the proposed system demonstrates its feasibility in coping with the variability in the brain-behavior relationship. In this contribution surprisingly simple EEG-based adaptive methods are used in combination with an ensemble scheme to significantly

关键词： Electroencephalography

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Enhanced symbolic regression through local variable transformations 9

Enhanced symbolic regression through local variable transfor...

引用

9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Kubalík, Jiří Derner, Erik Babuška, Robert Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague Czech Republic Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Cognitive Robotics Faculty of 3mE Delft University of Technology Delft Netherlands

ISBN: (纸本)9789897582745

Genetic programming (GP) is a technique widely used in a range of symbolic regression problems, in particular when there is no prior knowledge about the symbolic function sought. In this paper, we present a GP extension introducing a new concept of local transformed variables, based on a locally applied affine transformation of the original variables. This approach facilitates finding accurate parsimonious models. We have evaluated the proposed extension in the context of the Single Node Genetic Programming (SNGP) algorithm on synthetic as well as real-problem datasets. The results confirm our hypothesis that the transformed variables significantly improve the performance of the standard SNGP algorithm. © 2017 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Genetic programming

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Optimizing Disturbance Rejection by Using Model-Based Compensator with User-Defined High-Frequency Gains

Optimizing Disturbance Rejection by Using Model-Based Compen...

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APCA International Conference on Automatic control and Soft Computing (controlO)

作者： Damir Vrančić Paulo Moura Oliveira Mikulaš Huba Department of Systems and Control J. Stefan Institute Ljubljana Slovenia Department of Engineering Universidade de Trás-os-Montes e Alto Douro Portugal Faculty of Electrical engineering and information technology Slovak University of Technology Bratislava Slovakia

The paper presents extension of model-based disturbance rejection method based on Magnitude optimum method. The original method requires the pre-chosen values of controller and compensator filter values, which might result in a relatively noisy process input signals that are not tolerated in practice. In order to keep the process input noise under control, the proposed tuning method requires user-defined controller and compensator noise gain for high frequencies, instead. The experiments on process models show that the proposed approach is successful even though the actual and the identified process models do not match.

关键词： Process control Tuning Mathematical model Computational modeling Transfer functions Noise measurement Hybrid fiber coaxial cables

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Modeling and control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics During Grasping

Modeling and Control of Multi-Arm and Multi-Leg Robots: Comp...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Niels Dehio Joshua Smith Dennis Leroy Wigand Guiyang Xin Hsiu-Chin Lin Jochen J. Steil Michael Mistry Research Institute for Robotics and Process Control (IRP) Technical University Braunschweig Germany School of Informatics University of Edinburgh United Kingdom Faculty of Technology Bielefeld University Germany School of Mechanical and Electrical Engineering Central South University China

We consider a virtual manipulator in grasping scenarios which allows us to capture the effect of the object dynamics. This modeling approach turns a multi-arm robot into an underactuated system. We observe that controlling floating-base multi-leg robots is fundamentally similar. The Projected Inverse Dynamics control approach is employed for decoupling contact consistent motion generation and controlling contact wrenches. The proposed framework for underactuated robots has been evaluated on an enormous robot hand composed of four KUKA LWR IV+ representing fingers cooperatively manipulating a 9kg box with total 28 actuated DOF and six virtual DOF representing the object as additional free-floating robot link. Finally, we validate the same approach on ANYmal, a floating-base quadruped with 12 actuated DOF. Experiments are performed both in simulation and real world.

关键词： Grasping Dynamics Task analysis Jacobian matrices Manipulator dynamics

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