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检索条件"任意字段=5th IFAC Symposium on Modelling and Control in Biomedical Systems"

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Autotuning of a Robust Fractional Order PID controller

Autotuning of a Robust Fractional Order PID Controller

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Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： De Keyser, Robin Muresan, Cristina I. Ionescu, Clara M. Univ Ghent DySC Res Grp Dynam Syst & Control Ghent Belgium Tech Univ Cluj Napoca Dept Automat Cluj Napoca Romania

Fractional order PI/PD controllers are generalizations of the well-known PI/PD controllers with an extra parameter usually used to enhance the robustness of the closed loop system. In this paper, an autotuning method, referred to as the fractional order KC autotuner, is presented for tuning fractional order PI/PD controllers. the method is an extension of a previously presented autotuning principle and produces controllers, which are robust to system gain variations. Additionally, the method can also be adapted to obtain robust controllers to time delay, time constant variations, etc. the advantages of this autotuning method reside in the simplicity of the approach: 1) it requires solely one single sine test on the process;2) it does not need the process model and 3) it eliminates the complex nonlinear equations in the traditional fractional order controller design procedure. Numerical examples are included to validate the method. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： fractional order controllers autotuning method robustness iso-damping stability

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Interval Observer Design for Actuator Fault Estimation of Linear Parameter-Varying systems

Interval Observer Design for Actuator Fault Estimation of Li...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Lamouchi, Rihab Raissi, Tarek Amairi, Messaoud Aoun, Mohamed Conservatoire Natl Arts & Metiers Cedr Lab Paris France Univ Gabes MACS Lab Modeling Analy & Control Syst LR16ESS Natl Engn Sch Gabes ENIG Gabes Tunisia

this work is devoted to fault estimation of discrete-time Linear Parameter-Varying (LPV) systems subject to actuator additive faults and external disturbances. Under the assumption that the measurement noises and the disturbances are unknown but bounded, an interval observer is designed, based on decoupling the fault effect, to compute a lower and upper bounds for the unmeasured state and the faults. Stability conditions are expressed in terms of matrices inequalities. A case study is used to illustrate the effectiveness of the proposed approach. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Fault estimation Interval observer LPV system Unknown input observer

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modelling uncertainty for leak localization in Water Networks

Modelling uncertainty for leak localization in Water Network...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Blesa, Joaquim Perez, Ramon CSIC UPC Inst Robot & Informat Ind IRI C Llorens i Artigas 4-6 Barcelona 08028 Spain Univ Politecn Cataluna Res Ctr Supervis Safety & Automat Control CS2AC Terrassa CampusRambla St Nebridi 22 Barcelona 08222 Spain

the performance and success of model-based leak localization methods applied to water distribution networks (WDN) highly depends on the uncertainty of the system considered. this work proposes an original method of modeling the effect of uncertainties in these networks. the proposed method is based on the collection of real data in the water network in the absence of leaks. the discrepancy (residual) between the measured data and the one provided by a simulator of the network in normal operation is used to extrapolate the possible residuals in the different leak scenarios. In addition, indicators for assessing the effect of uncertainty in the performance of leak localization methods based on residual correlation analysis are provided. the error in terms of correlation intervals and leak localzation assessment between the proposed approximation and the real one is studied by means a simplified model of the WDN of Hanoi (Vietnam). (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： water distribution networks fault detection and izolation leak localzation correlation analysis

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On Switched controller Design for Robust control of Uncertain Polynomial Nonlinear systems Using Sum of Squares

On Switched Controller Design for Robust Control of Uncertai...

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Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： Ramos, Igor T. M. Alves, Uiliam N. L. T. de Oliveira, Diogo R. Teixeira, Marcelo C. M. Cardim, Rodrigo Machado, Erica R. M. D. Assuncao, Edvaldo Sao Paulo State Univ UNESP Sch Engn Dept Elect Engn Jose Carlos Rossi Ave 1970 BR-15385000 Ilha Solteira SP Brazil Fed Inst Educ Sci & Technol Mato Grosso Sul IFMS Angelo Melao St 790 BR-79641162 Tres Lagoas MS Brazil Fed Inst Educ Sci & Technol Parana IFPR Dr Tito Ave BR-86400000 Jacarezinho PR Brazil

this manuscript presents a switched control design for robust control of a class of uncertain nonlinear systems. In particular, it is considered a class of nonlinear systems whose dynamics are described by polynomial functions, that depend on the state vector of the system, with uncertain parameters. the design procedure can be represented in terms of sum of squares. the proposed switched control procedure uses a switching law to select at each instant of time a state-feedback polynomial gain, which belongs to a set of gains obtained from the proposed design procedure. the aim of the switching law is to choose a state-feedback polynomial gain that minimizes the time derivative of a polynomial Lyapunov function. A numerical example, using a chaotic Lorenz system with parametric uncertainties, illustrates the validity of the proposed approach. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Sum of squares (SOS) Robust control Uncertain nonlinear systems Switched systems Polynomial systems

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Annihilator design for linear parameter varying systems

Annihilator design for linear parameter varying systems

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Szabo, Z. Peni, T. Bokor, J. Hungarian Acad Sci Inst Comp Sci & Control Kende U 13-17 Budapest Hungary

Computation of the annihilator of a linear parameter-dependent (LPV) dynamical system is an important subtask in several fields of control theory, such as fault detection design or reconfigurable control design. While for LTI systems the problem can be efficiently handled, for LPV systems is not available a single algorithm that would provide the desired annihilator. thus alternative solutions are needed to handle the cases that might appear in applications. this paper provides new insights and additional technical details for the authors' previously proposed inversion based technique. As an alternative, for a special class of LPV systems where the parameter variation is affine, this paper provides an extension of the LTI techniques that computes the annihilator based on the geometric framework. A comparison of the two approaches gives an opportunity to illustrate some of the intricacies of the LPV modeling. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： LPV system null space geometric method

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A Novel Driver Performance Model Based on Machine Learning

A Novel Driver Performance Model Based on Machine Learning

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15th International-Federation-of-Automatic-control (ifac) symposium on control in Transportation systems (CTS)

作者： Aksjonov, Andrei Nedoma, Pavel Vodovozov, Valery Petlenkov, Eduard Herrmann, Martin SKODA Auto As Mlada Boleslav Czech Republic Tallinn Univ Technol Tallinn Estonia IPG Automot GmbH Karlsruhe Germany

Models of road vehicle driver behaviour are widely used in several disciplines, like driver distraction and autonomous driving. In this paper, a novel driver performance model, which is unique for every driver, is introduced. the driver is modelled with machine learning algorithms, namely artificial neural network and adaptive neuro-fuzzy inference system. Every model is trained and validated with the data collected during the real-time driver-in-the-loop experiment on a vehicle simulator for each driver separately. In total, 18 participants contributed to the experiment. Although the prediction accuracy of the models depends on the algorithm specifications, the artificial neural network was slightly more accurate in driver performance prediction comparing to the adaptive neuro-fuzzy inference system. the driver models may be used in detection of driver distraction induced by in-vehicle information system. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Neural fuzzy modelling and control Machine learning for environmental applications Vehicle dynamic systems Human factors in vehicular system Learning and adaptation in autonomous vehicles Safety

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Fault Detection and Fault Tolerance Mechanism for DC/DC Converters in Microgrids

Fault Detection and Fault Tolerance Mechanism for DC/DC Conv...

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10th ifac symposium on control of Power and Energy systems (CPES)

作者： Muresan, Vlad Moga, Daniel Petreus, Dorin Abrudean, Mihail Stroia, Nicoleta Moga, Rozica Tech Univ Cluj Napoca Cluj Napoca Romania

A solution for modelling and controlling the operation of DC/DC converters, both in normal and in fault regime, is proposed. the proposed converter model is based on ARX structure with variable coefficients. Feedforward fully connected neural network are used in order to generate the appropriate model coefficients for variable duty cycle. A control structure that can be used both to detect the faults and to reject their effect is introduced. the proposed structure contains a compensator whose action assures the avoidance of the unstable regime when the converter parameters change from their nominal values, acting as an efficient fault tolerance mechanism the proposed approach is directed toward developing algorithms suitable for real-time implementation on 32 bit ARM processors. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Power Electronics control Microgrids Operation of control of Renewable Energy systems

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Lead time prediction in a flow-shop environment with analytical and machine learning approaches

Lead time prediction in a flow-shop environment with analyti...

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16th ifac symposium on Information control Problems in Manufacturing (INCOM)

作者： Gyulai, David Pfeiffer, Andras Nick, Gabor Gallina, Viola Sihn, Wilfried Monostori, Laszlo Hungarian Acad Sci MTA Inst Comp Sci & Control SZTAKI Ctr Excellence Prod Informat & Control EPIC Budapest Hungary Fraunhofer Austria Res GmbH Vienna Austria

Manufacturing lead time (LT) is often among the most important corporate performance indicators that companies wish to minimize in order to meet the customer expectations, by delivering the right products in the shortest possible time. Most production planning and scheduling methods rely on LTs, therefore, the efficiency of these methods is crucially affected by the accuracy of LT prediction. However, achieving high accuracy is often complicated, due to the complexity of the processes and high variety of products. In the paper, analytical and machine learning prediction techniques are analyzed and compared, focusing on a real flow-shop environment exposed to frequent changes and uncertainties resulted by the changing customer order stream. the digital data twin of the processes is applied to accurately predict the manufacturing LT of jobs, keeping the prediction models up-to-date via online connection with the manufacturing execution system, and frequent retraining of the models. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Production control Lead time Manufacturing systems Machine learning Prediction methods Statistical inference

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Robust Model Predictive control: Implementation Issues with Comparative Analysis

Robust Model Predictive Control: Implementation Issues with ...

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Joint Meeting of the 2nd ifac Workshop on Linear Parameter Varying systems (LPVS) / 9th ifac symposium on Robust control Design (ROCOND)

作者： Gesser, Rodrigo S. Lima, Daniel M. Normey-Rico, Julio E. Univ Fed Santa Catarina Dept Automacao & Sistemas Florianopolis SC Brazil Univ Fed Santa Catarina Dept Engn Blumenau SC Brazil

Robust Model Predictive control (RMPC) is related to a variety of methods designed to guarantee control performance using optimization algorithms while considering systems with uncertainties. Many RMPC methods were created with different formulations, however there is lack of studies comparing their performances using pre-established metrics. thus, the objective of this paper is to analyze and compare different RMPC methods using a Continuous Stirred Tank Reactor (CSTR) plant with parametric uncertainties as a case of study. the methods are sorted by Min-max MPC, Tube-based MPC and LMI-based MPC, which were carefully chosen based on their relevance in the current literature. the metrics used to compare the methods are separated in off-line, related to configuration of the controller prior to its use, and on-line, which are related to the computational cost of the algorithm and difficulties that may arise during its application. Based on simulation results, it will be shown that the LMI-based methods are slower for calculating the control signal, but are easier to implement. Whereas, both Min-max and Tube-based methods require calculation of robust control invariant sets which might be difficult for more complex systems, however they are much faster when comparing to LMI. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Robust control Model Predictive control Uncertainty

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Fault-tolerant control of Linear Singularly Perturbed systems with Applications to Hypersonic Vehicles

Fault-tolerant Control of Linear Singularly Perturbed System...

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10th International-Federation-of-Automatic-control (ifac) symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

作者： Ren, Wenjing Jiang, Bin Yang, Hao Wen, Liyan Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Jiangsu Peoples R China

this paper studies the fault-tolerant control (FTC) problem of linear singular perturbed systems with component faults. Based on the analysis of two decomposed lower order subsystems, a composite fault-tolerant controller is designed to asymptotically stabilize the original impaired system through cooperative regulation of the control gains. An application to the longitudinal control system of a hypersonic vehicle with actuator faults is given. the singularly perturbed model of such a system is derived and a composite fault-tolerant controller is designed, which illustrates the effectiveness of the proposed method. (C) 2018, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Fault-tolerant control singular perturbation linear system hypersonic vehicle

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