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• 1.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory.
Institutionen för datavetenskap Linköpings universitet. Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Department of Computer Science University of Virginia.
Toward Adaptive Control of QoS-Importance Decoupled Real-Time Systems2007In: IEEE International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks,2007, 2007Conference paper (Refereed)

This paper deals with differentiated services in real-time systems. Tasks submitted to a real-time system are differentiated with respect to importance and QoS requirements. We use feedback control to enforce the requirements in QoS and ensure a hierarchical admission policy based on the importance of the tasks. The results show that the requirements are met during steady state when the workload is constant. The feedback control approach does not satisfactorily manage QoS when there is a sudden and significant workload change (transient state) due to the time-variant nature of the system. To address this, we present preliminary and promising results using adaptive control, and report on some challenges we are facing when applying the theory.

• 2.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
Software Engineering Institute, Carnegie Mellon University, USA. Dept. of Computer Science, University of Virginia, Charlottesville, USA. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Generalized performance management of multi-class real-time imprecise data services2005In: Real-Time Systems Symposium, 2005. RTSS 2005. 26th IEEE International, 2005, p. 12-49Conference paper (Other academic)

The intricacy of real-time data service management increases mainly due to the emergence of applications operating in open and unpredictable environments, increases in software complexity, and need for performance guarantees. In this paper we propose an approach for managing the quality of service of real-time databases that provide imprecise and differentiated services, and that operate in unpredictable environments. Transactions are classified into service classes according to their level of importance. Transactions within each service class are further classified into subclasses based on their quality of service requirements. In this way transactions are explicitly differentiated according to their importance and quality of service requests. The performance evaluation shows that during overloads the most important transactions are guaranteed to meet their deadlines and that reliable quality of service is provided even in the face of varying load and execution time estimation errors.

• 3.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA, USA. University of Virginia, USA.
Quantifying and Suppressing the Measurement Disturbance in Feedback Controlled Real-Time Systems2008In: Real-time systems, ISSN 0922-6443, E-ISSN 1573-1383, Vol. 40, no 1, p. 44-76Article in journal (Refereed)

In the control of continuous and physical systems, the controlled system is sampled sufficiently fast to capture the dynamics of the system. In general, this property cannot be applied to the control of computer systems as the measured variables are often computed over a data set, e.g., deadline miss ratio. In this paper we quantify the disturbance present in the measured variable as a function of the data set size and the sampling period, and we propose a feedback control structure that suppresses the measurement disturbance. The experiments we have carried out show that a controller using the proposed control structure outperforms a traditional control structure with regard to performance reliability.

• 4.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. University of Virginia, VA, USA.
Enhancing Feedback Control Scheduling Performance by On-line Quantification and Suppression of Measurement Disturbance2005In: Proceedings of the 11th IEEE Real-Time and Embedded Technology and Applications Symposium, 2005, p. 2-11Conference paper (Refereed)

In the control of continuous and physical systems, the controlled system is sampled sufficiently fast to capture the system dynamics. In general, this property cannot be applied to the control of computer systems as the measured variables are often computed over a data set, e.g., deadline miss ratio. In this paper we quantize the disturbance present in the measured variable as a function of the sampling period and we propose a measurement disturbance suppressive control structure. The experiments we have carried out show that a controller using the proposed control structure outperforms a traditional control structure with regard to performance reliability and adaptation.

• 5.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology. University of Virginia, USA. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Experimental Evaluation of Linear Time-Invariant Models for Feedback Performance Control in Real-Time Systems2007In: Real-time systems, ISSN 0922-6443, E-ISSN 1573-1383, Vol. 35, no 3, p. 209-238Article in journal (Refereed)

In recent years a new class of soft real-time applications operating in unpredictable environments has emerged. Typical for these applications is that neither the resource requirements nor the arrival rates of service requests are known or available a priori. It has been shown that feedback control is very effective to support the specified performance of dynamic systems that are both resource insufficient and exhibit unpredictable workloads. To efficiently use feedback control scheduling it is necessary to have a model that adequately describes the behavior of the system. In this paper we experimentally evaluate the accuracy of four linear time-invariant models used in the design of feedback controllers. We introduce a model (DYN) that captures additional system dynamics, which a previously published model (STA) fails to include. The accuracy of the models are evaluated by validating the models with regard to measured data from the controlled system and through a set of experiments where we evaluate the performance of a set of feedback control schedulers tuned using these models. From our evaluations we conclude that second order models (e.g., DYN) are more accurate than first order models (e.g. STA). Further we show that controllers tuned using second order models perform better than controllers tuned using first order models.

• 6.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
A Simulation and Animation Tool for Studying Multivariable Control2002In: Proceedings of the 15th IFAC World Congress, 2002, p. 1432-1432Conference paper (Refereed)

A simulation and animation tool for education in multivariable control is presented. The purpose of the tool is to support studies of various aspects of multivariable dynamical systems and design of multivariable feedback control systems. Different ways to use this kind of tool in control education are also presented and discussed.

• 7.
Queens University Belfast, United Kingdom.
Chalmers University of Technology, Sweden. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Massachusetts Institute of Technology, USA. Queens University, Canada.
Meeting the CDIO Requirements: An International Comparison of Engineering Curricula2006In: World Transactions on Engineering and Technology Education, ISSN 1446-2257, Vol. 5, no 2, p. 263-266Article in journal (Refereed)

In this article, the Conceive – Design – Implement – Operate (CDIO) Syllabus and CDIO Standards are introduced, and the question is posed as to whether or not national circumstances affect the ability of engineering programmes to meet CDIOrequirements. In particular, the extent to which representative programmes from the USA, Canada, Sweden and the UK cover the CDIO Syllabus is assessed and conclusions are drawn. The international applicability of the CDIO Syllabus also depends on the absence of conflict between the syllabus and national accreditation criteria. Based on the countries considered, the authors suggest that no conflict exists. Furthermore, it is argued that the CDIO Syllabus is aspirational and, as such, it complements the threshold requirements of national accreditation criteria. It is also argued that the CDIO Syllabus, coupled with the CDIO Standards, could form the basis for an international benchmark that would co-exist with any future global accreditation criteria and would serve to continuously improve engineering education.

• 8.
Universidade Federal de Minas Gerais, Brazil.
Robotics and Motion Division, ABB AB. Robotics and Motion Division, ABB AB. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Failure detection in robotic arms using  statistical modeling, machine learning and hybrid gradient boosting2018Report (Other academic)

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.

• 9.
Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology. Linköping University, The Institute of Technology.
The Development of the Applied Physics and Electrical Engineering (Y) Programme at Linköping University through Participation in the CDIO Initiative2005In: Proceedings of the 8th UICEE Annual Conference on Engineering Education, 2005, p. 321-324Conference paper (Refereed)
• 10.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Static Friction in a Robot Joint: Modeling and Identificaiton of Load and Temperature Effects2011Report (Other academic)

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.

• 11.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Static Friction in a Robot Joint: Modeling and Identification of Load and Temperature Effects2012In: Journal of Dynamic Systems Measurement, and Control, ISSN 0022-0434, E-ISSN 1528-9028, Vol. 134, no 5Article in journal (Refereed)

Friction is the result of complex interactions between contacting surfaces in down to a nanoscale perspective. Depending on the application, the different models available are more or less suitable. 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 functions of relevant states which are linear and nonlinear in the parameters, and how the identification method described in Golub and Pereyra (1973) can be used to identify them when all states are 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.

• 12.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
ABB Corporate Research. ABB Corporate Research. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
A Data-Driven Method for Monitoring of Repetitive Systems: Applications to Robust Wear Monitoring of a Robot Joint2013Report (Other academic)

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.

• 13.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
ABB Corporate Research, Västerås, Sweden. ABB Corporate Research, Västerås, Sweden. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. ABB Robotics, Västerås, Sweden.
A data-driven approach to diagnostics of repetitive processes in the distribution domain: Applications to gearbox diagnosticsin industrial robots and rotating machines2014In: Mechatronics (Oxford), ISSN 0957-4158, E-ISSN 1873-4006, Vol. 24, no 8, p. 1032-1041Article in journal (Refereed)

This paper presents a data-driven approach to diagnostics 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 an available 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 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 approach is demonstrated with successful experimental and simulation applications to wear diagnostics in an industrial robot gearbox and for diagnostics of gear faults in a rotating machine.

• 14.
Military Institute of Engineering, Brazil.
Military Institute of Engineering, Brazil. Military Institute of Engineering, Brazil. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Introduction of the CDIO Framework ay the Military Institue of Engineering in Brazil2016In: The 12th International CDIO Conference Proceedings – Full papers / [ed] Jerker Björkqvist, Kristina Edström, Ronald J. Hugo, Juha Kontio, Janne Roslöf, Rick Sellens & Seppo Virtanen, 2016Conference paper (Refereed)

This paper describes the motivation, the current state and the further actions of an improvement process of the engineering education at the Military Institute of Engineering (IME) in Brazil. Based on the reasons for why and how to change, the CDIO framework has been chosen as the kernel of this improvement process. The activities realized the plan of the further actions and the open questions are presented in this paper. The paper is a condensed presentation of the report (Cerqueira et. al., 2016), where a thorough background and more details can be found.

• 15.
Military Institute of Engineering, Brazil.
Military Institute of Engineering, Brazil. Military Institute of Engineering, Brazil. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Introducing CDIO at The Military Institue of Engineering in Brazil2016Report (Other academic)

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.

• 16.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
The CDIO Initiative from an Automatic Control Project Course Perspective2005In: Proceedings of the 16th IFAC World Congress, 2005, p. 2283-2283Conference paper (Refereed)

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.

• 17.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
The CDIO Initiative from an Automatic Control Project Course Perspective2004Report (Other academic)

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.

• 18.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory2005In: Proceedings of the 16th IFAC World Congress, 2005, p. 609-609Conference paper (Refereed)

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.

• 19.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory2004Report (Other academic)

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.

• 20.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Automatic Control Education in a CDIO Perspective2017In: 20th IFAC World Congress, Elsevier, 2017, Vol. 50(1), no 1, p. 12161-12166Conference paper (Refereed)

The CDIO framework for development of engineering education is presented, including the overall ideas, the fundamental documents, and some development tools. The automatic control subject and its role in engineering education is studied using the CDIO Standards as reference. Some examples from the engineering education at Linkoping University are presented with special focus on the control education. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

• 21.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Combining Tracking and Regularization in Recursive Least Squares Identification1996In: Proceedings of the 35th IEEE Conference on Decision and Control, 1996, p. 2551-2552 vol.3Conference paper (Refereed)

The combination of tracking and regularization in recursive identification is studied. It is shown that regularization of the information matrix corresponds to a normalization of the covariance matrix, and that several of the proposed methods for dealing with covariance matrix blow up can be interpreted as approximate implementations of covariance matrix normalization.

• 22.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Combining Tracking and Regularization in Recursive Least Squares Identification1996Report (Other academic)

The combination of tracking and regularization in recursive identification is studied. It is shown that regularization of the information matrix corresponds to a normalization of the covariance matrix, and that several of the proposed methods for dealing with covariance matrix blow up can be interpreted as approximate implementations of covariance matrix normalization.

• 23.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Frequency Domain Accuracy of Recursively Identified ARX Models1991In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 54, no 2, p. 465-480Article in journal (Refereed)

Recursive identification of time varying systems using ARX models is considered, with focus on the accuracy of the transfer function estimates. Three recursive identification algorithms are studied, the least mean squares algorithm, the recursive least squares algorithm and the Kalman filter respectively. The model accuracy is studied in terms of algorithm design variables, input and disturbance signal properties and variations of the true system. Using asymptotic methods approximate expressions for the model quality are derived. The derived expressions are validated by simulations.

• 24.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Frequency Domain Aspects of Modeling and Control in Adaptive Systems1988Doctoral thesis, monograph (Other academic)

In this thesis various aspects of modeling and control in adaptive systems are presented from a frequency domain viewpoint.

The thesis consists of three parts, where the first part contains a general introduction and background information concerning the problems that will be treated. In the second part some recursive identification algorithms are studied with respect to their ability to track time-varying systems and their disturbance sensitivity. Simple and illustrative frequency domain expressions that describe these properties are derived using asymptotic methods. The algorithms that are treated are the constant gain gradient (LMS) algorithm, the recursive least squares algorithm with constant forgetting factor and the Kalman filter respectively. The behavior of these methods when applied to FIR and ARX systems are studied. In the third part of the thesis adaptive control based on low order models is studied. The adaptive control algorithm that is investigated is the recursive least squares algorithm combined with pole placement regulator design. Starting from frequency domain expressions, that describe how a low order model obtained by system identification approximates a higher order system, the consequences for adaptive control are investigated. It is shown how a proper use of filtering in the identification part of the adaptive regulator can improve the robustness properties of the adaptive regulator with respect to unmodelled dynamics.

• 25.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Frequency Domain Description of the Quality of Recursively Identified FIR Models in the Presence of Correlated Disturbances1990Report (Other academic)
• 26.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Model Quality in Recursive Identification of Time Varying Systems with ARX Structure1990In: Proceedings of the 1990 American Control Conference, 1990, p. 1909-1914Conference paper (Refereed)

Recursive identification of time varying systems with ARX structures is considered, with the interest focused on the quality of the estimated transfer functions. Three recursive identification algorithms are considered, the least mean squares (LMS) algorithm, the recursive least squares (RLS) algorithm and the Kalman filter respectively. The model quality is studied in terms of algorithm design variables, input and disturbance signal properties and variations of the true system. Using asymptotic methods approximate expressions for the model quality are derived.

• 27.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Model Quality in Recursive Identification of Time Varying Systems with ARX Structure1990Report (Other academic)

Recursive identification of time varying systems with ARX structures is considered, with the interest focused on the quality of the estimated transfer functions. Three recursive identification algorithms are considered, the least mean squares (LMS) algorithm, the recursive least squares (RLS) algorithm and the Kalman filter respectively. The model quality is studied in terms of algorithm design variables, input and disturbance signal properties and variations of the true system. Using asymptotic methods approximate expressions for the model quality are derived.

• 28.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On Covariance Modification and Regularization in Recursive Least Squares Identification1994In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, p. 661-666Conference paper (Refereed)

In this paper the relationships between covariance modification and regularization in recursive least squares identification are investigated. An update equation for the information matrix is derived and it is shown how regularization of the information matrix can be expressed as a particular type of covariance matrix modification. The paper also presents an analysis of the effects of a covariance modification for obtaining regularization that was proposed in Salgado et al. (1988)

• 29.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On Identification of a Flexible Mechanical System using Decimated Data2005In: Proceedings of the 16th IFAC World Congress, 2005, p. 12-12Conference paper (Refereed)

System identification of a flexible mechanical system using decimated data is studied. It is illustrated how the use of decimated data can give erroneous results due to the inter-sample behavior of the signals, and an intuitive explanation to this phenomenon is proposed. The possible improvement by using alternative assumptions for the inter-sample behavior is investigated.

• 30.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On Identification of a Flexible Mechanical System using Decimated Data2004Report (Other academic)

System identification of a flexible mechanical system using decimated data is studied. It is illustrated how the use of decimated data can give erroneous results due to the inter-sample behavior of the signals, and an intuitive explanation to this phenomenon is proposed. The possible improvement by using alternative assumptions for the inter-sample behavior is investigated.

• 31.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On some Asymptotic Uncertainty Bounds in Recursive Least Squares Identification1992Report (Other academic)

This note deals with the performance of the recursive least squares algorithm when it is applied to problems where the measured signal is corrupted by bounded noise. Using ideas from bounding ellipsoid algorithms we derive an asymptotic expression for the bound on the uncertainty of the parameter estimate for a simple choice of design variables. This bound is also transformed to a bound on the uncertainty of the transfer function estimate.

• 32.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On Some Asymptotic Uncertainty Bounds in Recursive Least Squares Identification1993In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 38, no 11, p. 1685-1688Article in journal (Refereed)

This note deals with the performance of the recursive least squares algorithm when it is applied to problems where the measured signal is corrupted by bounded noise. Using ideas from bounding ellipsoid algorithms we derive an asymptotic expression for the bound on the uncertainty of the parameter estimate for a simple choice of design variables. This bound is also transformed to a bound on the uncertainty of the transfer function estimate.

• 33.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On Some Updating Strategies in Recursive Least Squares Identification1991Report (Other academic)
• 34.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Mean Square Error of Transfer Function Estimates with Applications to Control1986Licentiate thesis, monograph (Other academic)

In this report we study the mean square error of transfer function estimates obtained by identification. The model quality is related to the use of models in regulator design, and the properties of affecting the bias part of the mean square error, both in fixed parameter control and adaptive control.

We also study the variance part of the mean square error for transfer function estimates obtained by recursive identification. In the report we derive expressions for the variance as a function of the step length of the identification method, the input spectrum, the variations of the true system and the model order. These expressions are verified and utilized in simulations.

• 35.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Performance of the Recursive Least Squares Method in the Presence of Bounded Disturbances1991In: Proceedings of the 30th IEEE Conference on Decision and Control, 1991, Vol. 1, p. 762-763 vol.1Conference paper (Refereed)

The author considers the performance of the recursive least squares method when applied to problems where the measured signal is corrupted by noise, which is bounded but otherwise of unknown characteristics. An asymptotic expression for the bound on the parameter estimation error is derived using ideas from bounding ellipsoid algorithms.

• 36.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Performance of the Recursive Least Squares Method in the Presence of Bounded Disturbances1991Report (Other academic)

The author considers the performance of the recursive least squares method when applied to problems where the measured signal is corrupted by noise, which is bounded but otherwise of unknown characteristics. An asymptotic expression for the bound on the parameter estimation error is derived using ideas from bounding ellipsoid algorithms.

• 37.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Properties of Pole Placement Regulators1986In: Proceedings of the 25th IEEE Conference on Decision and Control, 1986, p. 114-116Conference paper (Refereed)

The frequency domain properties of pole placement regulators are studied, and the influence of the regulator on the model quality is discussed. Some methods to affect the regulator properties are discussed.

• 38.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Properties of Pole Placement Regulators1987Report (Other academic)

The frequency domain properties of pole placement regulators are studied, and the influence of the regulator on the model quality is discussed. Some methods to affect the regulator properties are discussed.

• 39.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Quality of Recursively Identified FIR Models1992In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 40, no 3, p. 679-682Article in journal (Refereed)

The author considers recursive identification of time-varying systems having finite impulse response, focusing on the tradeoff between tracking capability and disturbance rejection. Approximate, but simple and explicit, frequency-domain expressions for the model quality are derived for three different identification algorithms. The results, derived under the assumption of slow adaptation, slow system variation, and high model order, are extensions of the results presented by Gunnarsson and Ljung (see ibid., vol.37, p.1072, 1989) to the case where the system output is affected by correlated disturbances.

• 40.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Variance of Recursive Transfer Function Estimates of Systems with FIR-Structure1986In: Proceedings of the 25th IEEE Conference on Decision and Control, 1986, p. 2029-2030Conference paper (Refereed)

The variance of recursive transfer function estimates for systems with finite impulse response structure is studied. Expressions for the variance are derived using asymptotic methods. The variance expressions explicitly show the influence of step length, input spectrum, noise variance, parameter variations and model order.

• 41.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
On the Variance of Recursive Transfer Function Estimates with FIR-Structure1987Report (Other academic)

The variance of recursive transfer function estimates for systems with finite impulse response structure is studied. Expressions for the variance are derived using asymptotic methods. The variance expressions explicitly show the influence of step length, input spectrum, noise variance, parameter variations and model order.

• 42.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Robustness in Adaptive Control from a Frequency Domain System Identification Perspective1989In: Proceedings of the 1989 IFAC Symposium on Adaptive Control and Signal Processing, 1989, p. 433-437Conference paper (Refereed)
• 43.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Robustness in Adaptive Control from a Frequency Domain System Identification Perspective1988Report (Other academic)
• 44.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, RTSLAB - Real-Time Systems Laboratory. Linköping University, The Institute of Technology. University of Virginia, Charlottesville, USA.
Robust Quality Management for Differentiated Imprecise Data Services2004In: Proceedings of the 25th IEEE International Real-Time Systems Symposium, 2004, p. 265-275Conference paper (Refereed)

Several applications, such as Web services and e-commerce, are operating in open environments where the workload characteristics, such as the load applied on the system and the worst-case execution times, are inaccurate or even not known in advance. This implies that transactions submitted to a real-time database cannot be subject to exact schedulability analysis given the lack of a priori knowledge of the workload. In this paper we propose an approach, based on feedback control, for managing the quality of service of real-time databases that provide imprecise and differentiated services, given inaccurate workload characteristics. For each service class, the database operator specifies the quality of service requirements by explicitly declaring the precision requirements of the data and the results of the transactions. The performance evaluation shows that our approach provides reliable quality of service even in the face of varying load and inaccurate execution time estimates.

• 45.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology. Linköping University.
Redesign of the Applied Physics and Electrical Engineering Program at Linköping University According to CDIO2005In: Proceedings of the 33rd SEFI Annual Conference, 2005, p. 260-Conference paper (Refereed)
• 46.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Université Catholique de Louvain, Belgium. Université Catholique de Louvain, Belgium.
Tuning of a Decoupling Controller for a 2×2 System using Iterative Feedback Tuning2003In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 11, no 9, p. 1035-1041Article in journal (Refereed)

Iterative feedback tuning is used to tune a decoupling controller for a 2 × 2 multivariable system. The tuning is carried out in two steps. In the first step the coefficients of two proportional decoupling controllers are tuned, and in the second step two PD-controllers are tuned. The approach is evaluated on a nonlinear simulation model of a two-link manipulator. The evaluation is carried out using two different reference trajectories and also in the presence of friction. The resulting closed loop systems show satisfactory behavior in all three cases.

• 47.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, The Institute of Technology. Linköping University, The Institute of Technology. Linköping University, The Institute of Technology. Technical University of Denmark, Denmark. Technical University of Denmark, Denmark.
Using the CDIO Syllabus in Formulation of Program Goals - Experiences and Comparisons2009In: Proceedings of the 5th International CDIO Conference, 2009Conference paper (Refereed)

This paper presents experiences and results from large scale and systematic use of the CDIO Syllabus for developing program goals and formulating learning outcomes at Linköping University (LiU), Sweden, and Technical University of Denmark (DTU). The approaches are based on the use of tools for program design such as ITU-matrices and skill progression matrices. During the process local adaptations of the Syllabus have been made in order to meet regulations by authorities in higher education as well as to cover programs in related areas as natural sciences. The experiences are that the CDIO Syllabus is a very useful tool in this process and that the way of organizing the management of the education programs is important for success as well as support from students, faculty members and stakeholders.

• 48.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Some Aspects of Iterative Identification and Control Design Schemes1994Report (Other academic)

In this report we study some different aspects of schemes for iterative identification and control design. By formulating the control objective as a criterion minimization task the problem of finding a model well suited for control appears to be closely related to a prediction error minimization problem in system identification. We discuss two ways of matching the control and identification criteria and evaluate their properties in simulations.

• 49.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
IO (Implement and Operate) First in an Automatic Control Context2016In: Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016 / [ed] Jerker Björkqvist, Kristina Edström, Ronald J. Hugo, Juha Kontio, Janne Roslöf, Rick Sellens & Seppo Virtanen, CDIO , 2016, p. 238-249Conference paper (Refereed)

A first course in Automatic control is presented.  A main objective of the course is to put most of the emphasis on the Implement and Operate phases in the process of developing a control system for a process. The course is built around a large amount of student active learning based on three extensive laboratory exercises, where each laboratory exercise can have duration of up to two weeks. For each of the laboratory exercises there is a sequence of learning activities supporting the students’ learning: Introductory lecture, problem solving session, preparation work, help-desk session, independent work in the laboratory, and a final demonstration of the control system. In addition there is a small project where the task is to write a manual for a process operator. The laboratory tasks involve implementation of a control system in an industrial PLC (Programmable Logic Controller) and development of an operator interface.

• 50.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Computer Supported Learning and Assessment in Engineering Education2008In: Proceedings of the 4th International CDIO Conference, 2008Conference paper (Refereed)

Some aspects of computer support in learning and assessment in engineering education are discussed. It is emphasized that the use of computer support, like e.g. simulations, computations, visualizations, has to be closely connected to the formulation of the expected learning outcomes and the assessment methods. Some examples of computer support are related to the CDIO Syllabus. Some experiences from more that two decades of computer aided learning and assessment within the Division of Automatic Control at Linköping University are presented

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