| 1. |
- Azevedo Costa, Marcelo, et al.
(author)
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Failure detection in robotic arms using statistical modeling, machine learning and hybrid gradient boosting
- 2018
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Reports (other academic/artistic)abstract
- Modeling and failure prediction is an important task in manyengineering systems. For this task, the machine learning literaturepresents a large variety of models such as classification trees,random forest, artificial neural networks, fuzzy systems, amongothers. In addition, standard statistical models can be applied suchas the logistic regression, linear discriminant analysis, $k$-nearestneighbors, among others. This work evaluates advantages andlimitations of statistical and machine learning methods to predictfailures in industrial robots. The work is based on data from morethan five thousand robots in industrial use. Furthermore, a newapproach combining standard statistical and machine learning models,named \emph{hybrid gradient boosting}, is proposed. Results show thatthe a priori treatment of the database, i.e., outlier analysis,consistent database analysis and anomaly analysis have shown to becrucial to improve classification performance for statistical, machinelearning and hybrid models. Furthermore, local joint information hasbeen identified as the main driver for failure detection whereasfailure classification can be improved using additional informationfrom different joints and hybrid models.
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| 2. |
- Carvalho Bittencourt, André, 1984-, et al.
(author)
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A Data-Driven Method for Monitoring of Repetitive Systems: Applications to Robust Wear Monitoring of a Robot Joint
- 2013
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Reports (other academic/artistic)abstract
- This paper presents a method for monitoring of systems that operate in a repetitive manner. Considering that data batches collected from a repetitive operation will be similar unless in the presence of an abnormality, a condition change is inferred by comparing the monitored data against a nominal batch. The method proposed considers the comparison of data in the distribution domain, which reveals information of the data amplitude. This is achieved with the use of kernel density estimates and the Kullback-Leibler distance. To decrease sensitivity to unknown disturbances while increasing sensitivity to faults, the use of a weighting vector is suggested which is chosen based on a labeled dataset. The framework is simple to implement and can be used without process interruption, in a batch manner. The method was developed with interests in industrial robotics where a repetitive behavior is commonly found. The problem of wear monitoring in a robot joint is studied based on data collected from a test-cycle. Real data from accelerated wear tests and simulations are considered. Promising results are achieved where the method output shows a clear response to the wear increases.
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| 3. |
- Carvalho Bittencourt, André, et al.
(author)
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Static Friction in a Robot Joint : Modeling and Identificaiton of Load and Temperature Effects
- 2011
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Reports (other academic/artistic)abstract
- Friction is the result of complex interactions between contacting surfaces in a nanoscale perspective. Depending on the application, the different models available are more or less suitable. Available static friction models are typically considered to be dependent only on relative speed of interacting surfaces. However, it is known that friction can be affected by other factors than speed. In this paper, the typical friction phenomena and models used in robotics are reviewed. It is shown how such models can be represented as a sum of linear and nonlinear functions of relevant states, and how the identification method described in [1] can be used to identify them when all state sare measured. The discussion follows with a detailed experimental study of friction in a robot joint under changes of joint angle, load torque and temperature. Justified by their significance, load torque and temperature are included in an extended static friction model. The proposed model is validated in a wide operating range, considerably improving the prediction performance compared to a standard model.
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| 4. |
- Cerqueira, Jorge, et al.
(author)
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Introducing CDIO at The Military Institue of Engineering in Brazil
- 2016
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Reports (other academic/artistic)abstract
- This report describes the motivation, the current state and the future actions of an improvement process in engineering education at the Brazilian higher education institution called the Military Institute of Engineering. Based on the reasons for why and how to change, the CDIO framework was chosen, at the end of 2014, as the kernel of this improvement process. The activities realized, the plan for the future actions and the open questions are presented in this report.
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| 5. |
- Enqvist, Martin, 1976-, et al.
(author)
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The CDIO Initiative from an Automatic Control Project Course Perspective
- 2004
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Reports (other academic/artistic)abstract
- The CDIO (Conceive Design Implement Operate) Initiative is explained, and some of the results at the Applied Physics and Electrical Engineering program at Linköping University, Sweden, are presented. A project course in Automatic Control is used as an example. The projects within the course are carried out using the LIPS (Linköping interactive project steering) model. An example of a project, the golf playing industrial robot, and the results from this project are also covered.
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| 6. |
- Fujimori, Atsushi, et al.
(author)
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A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory
- 2004
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Reports (other academic/artistic)abstract
- This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.
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| 7. |
- Gunnarsson, Svante, et al.
(author)
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A Short Introduction to Iterative Learning Control
- 1997
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Reports (other academic/artistic)abstract
- An introduction to Iterative Learning Control (ILC) is given. The basic principle behind ILC in both open loop and closed loop problems is explained. A general class of algorithms for updating of the ILC input signal is presented and the choice of the filters in the update algortihm is discussed with respect to convergence, robustness and disturbance sensitivity.
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| 8. |
- Gunnarsson, Svante, et al.
(author)
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Adaptive Compensation of Deformations in Mechanical Structures Controlled by Hydraulic Actuators
- 1989
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Reports (other academic/artistic)abstract
- In servo applications involving complex mechanical structures load forces often cause deformations in the structure. Since normally only the actuator position is measured and fed back to the control unit the deformations will introduce errors in the positioning of the load. The approach proposed in this paper is to estimate the true load position. If the stiffness between the actuator and the load is known it is possible to estimate the position of the load by measuring the actuator force/pressure. The estimation of the stiffness is based on recursive identification of the dynamics between actuator force and actuator pressure. The identified model can be used to improve the dynamic properties of the system as well as to compensate for the static error.
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| 9. |
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| 10. |
- Gunnarsson, Svante, et al.
(author)
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Computer Supported Control Education from a Linköping Perspective
- 1997
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Reports (other academic/artistic)abstract
- The development of computer supported control education at Linköping University is presented. A review of the different phases of development of computer support is given. The experiences from the introduction of computer supported exams are discussed.
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