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Paul, S., Yu, W. & Li, X. (2019). Discrete-time sliding mode for building structure bidirectional active vibration control. Transactions of the Institute of Measurement and Control, 41(2), 433-446
Open this publication in new window or tab >>Discrete-time sliding mode for building structure bidirectional active vibration control
2019 (English)In: Transactions of the Institute of Measurement and Control, ISSN 0142-3312, E-ISSN 1477-0369, Vol. 41, no 2, p. 433-446Article in journal (Refereed) Published
Abstract [en]

In terms of vibrations along bidirectional earthquake forces, several problems are faced when modelling and controlling the structure of a building, such as lateral-torsional vibration, uncertainties surrounding the rigidity and the difficulty of estimating damping forces.In this paper, we use a fuzzy logic model to identify and compensate the uncertainty which does not require an exact model of the building structure. To attenuate bidirectional vibration, a novel discrete-time sliding mode control is proposed. This sliding mode control has time-varying gain and is combined with fuzzy sliding mode control in order to reduce the chattering of the sliding mode control. We prove that the closed-loop system is uniformly stable using Lyapunov stability analysis. We compare our fuzzy sliding mode control with the traditional controllers: proportional?integral?derivative and sliding mode control. Experimental results show significant vibration attenuation with our fuzzy sliding mode control and horizontal-torsional actuators. The proposed control system is the most efficient at mitigating bidirectional and torsional vibrations.

Place, publisher, year, edition, pages
Sage Publications Ltd., 2019
Keywords
Active vibration control, sliding mode control, discrete-time
National Category
Engineering and Technology Control Engineering
Identifiers
urn:nbn:se:oru:diva-71777 (URN)10.1177/0142331218764581 (DOI)000456729000011 ()
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-06-18Bibliographically approved
Jafari, R., Razvarz, S., Gegov, A. & Paul, S. (2019). Fuzzy Modeling for Uncertain Nonlinear Systems Using Fuzzy Equations and Z-Numbers. In: Lotfi, Ahmad; Bouchachia, Hamid; Gegov, Alexander; Langensiepen, Caroline; McGinnity, Martin (Ed.), Advances in Intelligent Systems and Computing: . Paper presented at UK Workshop on Computational Intelligence (UKCI), Nottingham, UK, September 5-7, 2018 (pp. 96-107). Springer, 840
Open this publication in new window or tab >>Fuzzy Modeling for Uncertain Nonlinear Systems Using Fuzzy Equations and Z-Numbers
2019 (English)In: Advances in Intelligent Systems and Computing / [ed] Lotfi, Ahmad; Bouchachia, Hamid; Gegov, Alexander; Langensiepen, Caroline; McGinnity, Martin, Springer, 2019, Vol. 840, p. 96-107Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, the uncertainty property is represented by Z-number as the coefficients and variables of the fuzzy equation. This modification for the fuzzy equation is suitable for nonlinear system modeling with uncertain parameters. Here, we use fuzzy equations as the models for the uncertain nonlinear systems. The modeling of the uncertain nonlinear systems is to find the coefficients of the fuzzy equation. However, it is very difficult to obtain Z-number coefficients of the fuzzy equations.

Taking into consideration the modeling case at par with uncertain nonlinear systems, the implementation of neural network technique is contributed in the complex way of dealing the appropriate coefficients of the fuzzy equations. We use the neural network method to approximate Z-number coefficients of the fuzzy equations.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Fuzzy modeling, Z-number, Uncertain nonlinear system
National Category
Computational Mathematics Control Engineering
Identifiers
urn:nbn:se:oru:diva-71789 (URN)10.1007/978-3-319-97982-3_8 (DOI)2-s2.0-85052217113 (Scopus ID)
Conference
UK Workshop on Computational Intelligence (UKCI), Nottingham, UK, September 5-7, 2018
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-02-01Bibliographically approved
Jafari, R., Razvarz, S., Gegov, A., Paul, S. & Keshtkar, S. (2019). Fuzzy Sumudu Transform Approach to Solving Fuzzy Differential Equations With Z-Numbers. In: Mangey Ram (Ed.), Advanced Fuzzy Logic Approaches in Engineering Science: (pp. 18-48). Hershey, PA, USA: IGI Global
Open this publication in new window or tab >>Fuzzy Sumudu Transform Approach to Solving Fuzzy Differential Equations With Z-Numbers
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2019 (English)In: Advanced Fuzzy Logic Approaches in Engineering Science / [ed] Mangey Ram, Hershey, PA, USA: IGI Global , 2019, p. 18-48Chapter in book (Other academic)
Abstract [en]

Uncertain nonlinear systems can be modeled with fuzzy differential equations (FDEs) and the solutions of these equations are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this book chapter, the solutions of FDEs are approximated by utilizing the fuzzy Sumudu transform (FST) method. Here, the uncertainties are in the sense of fuzzy numbers and Z-numbers. Important theorems are laid down to illustrate the properties of FST. This new technique is compared with Average Euler method and Max-Min Euler method. The theoretical analysis and simulation results show that the FST method is effective in estimating the solutions of FDEs.

Place, publisher, year, edition, pages
Hershey, PA, USA: IGI Global, 2019
National Category
Engineering and Technology Computational Mathematics Mathematical Analysis
Identifiers
urn:nbn:se:oru:diva-71791 (URN)10.4018/978-1-5225-5709-8.ch002 (DOI)
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
Paul, S., Yu, W. & Jafari, R. (2019). Stability analysis and bidirectional vibration control of structure. In: Lecture Notes in Civil Engineering: . Springer
Open this publication in new window or tab >>Stability analysis and bidirectional vibration control of structure
2019 (English)In: Lecture Notes in Civil Engineering, Springer, 2019Chapter in book (Refereed)
Place, publisher, year, edition, pages
Springer, 2019
National Category
Engineering and Technology
Identifiers
urn:nbn:se:oru:diva-71799 (URN)
Available from: 2019-01-24 Created: 2019-01-24 Last updated: 2019-02-01
Paul, S. & Yu, W. (2018). A method for bidirectional active control of structures. Journal of Vibration and Control, 24(15), 3400-3417
Open this publication in new window or tab >>A method for bidirectional active control of structures
2018 (English)In: Journal of Vibration and Control, ISSN 1077-5463, E-ISSN 1741-2986, Vol. 24, no 15, p. 3400-3417Article in journal (Refereed) Published
Abstract [en]

Proportional-derivative (PD) and proportional-integral-derivative (PID) controllers are popular control algorithms in industrial applications, especially in structural vibration control. In this paper, the designs of two dampers, namely the horizontal actuator and torsional actuator, are combined for the lateral and torsional vibrations of the structure. The standard PD and PID controllers are utilized for active vibration control. The sufficient conditions for asymptotic stability of these controllers are validated by utilizing the Lyapunov stability theorem. An active vibration control system with two floors equipped with a horizontal actuator and a torsional actuator is installed to carry out the experimental analysis. The experimental results show that bidirectional active control has been achieved.

Place, publisher, year, edition, pages
Sage Publications, 2018
Keywords
PID control, bidirectional control, active vibration control, stability, building structure
National Category
Engineering and Technology Control Engineering
Identifiers
urn:nbn:se:oru:diva-71776 (URN)10.1177/1077546317705556 (DOI)000441274200012 ()2-s2.0-85045343337 (Scopus ID)
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
Paul, S., Yu, W. & Jafari, R. (2018). A method for bidirectional active vibration control of structure using discrete-time sliding mode. Paper presented at 2nd IFAC Conference on Modelling, Identification and Control of Nonlinear Systems MICNON, Guadalajara, Jalisco, Mexico, June 20-22, 2018. IFAC-PapersOnLine, 51(13), 361-365
Open this publication in new window or tab >>A method for bidirectional active vibration control of structure using discrete-time sliding mode
2018 (English)In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 13, p. 361-365Article in journal (Refereed) Published
Abstract [en]

In this paper, a novel discrete-time sliding mode control is proposed in order to attenuate structural vibration due to earthquake forces. The analysis is based on the lateral-torsional vibration under the bidirectional waves. The proposed fuzzy modeling based sliding mode control can reduce chattering due to its time-varying gain. In the modeling equation of the structural system, the uncertainty exists in terms of sti¤ness, damping forces and earthquake. Fuzzy logic model is used to identify and compensate the uncertainty associated with the modeling equation. We prove that the closed-loop system is uniformly stable using Lyapunov stability analysis. The experimental result reveals that discrete-time sliding mode controller offers significant vibration attenuation with active mass damper and torsional actuator.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
active vibration control, sliding mode control, discrete-time, Lyapunov stability, fuzzy logic
National Category
Engineering and Technology Control Engineering
Identifiers
urn:nbn:se:oru:diva-71780 (URN)10.1016/j.ifacol.2018.07.305 (DOI)000443321500060 ()2-s2.0-85052620438 (Scopus ID)
Conference
2nd IFAC Conference on Modelling, Identification and Control of Nonlinear Systems MICNON, Guadalajara, Jalisco, Mexico, June 20-22, 2018
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
Paul, S. & Morales-Menendez, R. (2018). Active Control of Chatter in Milling Process Using Intelligent PD/PID Control. IEEE Access, 6, 72698-72713
Open this publication in new window or tab >>Active Control of Chatter in Milling Process Using Intelligent PD/PID Control
2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 72698-72713Article in journal (Refereed) Published
Abstract [en]

Chatter is an obstacle for achieving high-quality machining process and high production rate in industries. Chatter is an unstable self-exciting phenomenon that leads to tool wear, poor surface finish, and downgrade the milling operations. A novel active control strategy to attenuate the chatter vibration is proposed. PD/PID controllers in combination with Type-2 Fuzzy logic were utilized as a control strategy. The main control actions were generated by PD/PID controllers, whereas the Type-2 Fuzzy logic system was used to compensate the involved nonlinearities. The Lyapunov stability analysis was utilized to validate the stability of Fuzzy PD/PID controllers. The theoretical concepts and results are proved using numerical simulations. Although PD/PID controllers have been used for chatter control in machining process, the importance of stability along with the implementation of Type-2 Fuzzy logic system for nonlinearity compensation was the main contribution. In addition, active control using an Active Vibration Damper placed in an effective position is entirely a new approach with promising practical results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Milling, Shock absorbers, Tools, Fuzzy logic, Vibrations, Force, Vibration control, manufacturing, fuzzy control, PD control, Lyapunov methods, stability analysis, control nonlinearities
National Category
Control Engineering
Identifiers
urn:nbn:se:oru:diva-71771 (URN)10.1109/ACCESS.2018.2882491 (DOI)000454057900001 ()2-s2.0-85057167148 (Scopus ID)
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
Paul, S., Yu, W. & Li, X. (2018). Bidirectional active control of structures with type-2 fuzzy PD and PID. International Journal of Systems Science, 49(4), 766-782
Open this publication in new window or tab >>Bidirectional active control of structures with type-2 fuzzy PD and PID
2018 (English)In: International Journal of Systems Science, ISSN 0020-7721, E-ISSN 1464-5319, Vol. 49, no 4, p. 766-782Article in journal (Refereed) Published
Abstract [en]

Proportional-derivative and proportional-integral-derivative (PD/PID) controllers are popular algorithms in structure vibration control. In order to maintain minimum regulation error, the PD/PID control require big proportional and derivative gains. The control performances are not satisfied because of the big uncertainties in the buildings. In this paper, type-2 fuzzy system is applied to compensate the unknown uncertainties, and is combined with the PD/PID control. We prove the stability of these fuzzy PD and PID controllers. The sufficient conditions can be used for choosing the gains of PD/PID. The theory results are verified by a two-storey building prototype. The experimental results validate our analysis.

Place, publisher, year, edition, pages
Taylor & Francis, 2018
Keywords
Active control of structures, stability, PID control, type-2 fuzzy system
National Category
Control Engineering
Identifiers
urn:nbn:se:oru:diva-71772 (URN)10.1080/00207721.2017.1421724 (DOI)000424792000007 ()2-s2.0-85040963139 (Scopus ID)
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
Jafari, R., Razvarz, S., Gegov, A. & Paul, S. (2018). Modeling and Control of Uncertain Nonlinear Systems. In: : . Paper presented at 9th International Conference on Intelligent Systems, Madeira Island, Portugal, September 25-27, 2018. IEEE
Open this publication in new window or tab >>Modeling and Control of Uncertain Nonlinear Systems
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

A survey of the methodologies associated with the modeling and control of uncertain nonlinear systems has been given due importance in this paper. The basic criteria that highlights the work is relied on the various patterns of techniques incorporated for the solutions of fuzzy equations that corresponds to fuzzy controllability subject. The solutions which are generated by these equations are considered to be the controllers. Currently, numerical techniques have come out as superior techniques in order to solve these types of problems. The implementation of neural networks technique is contributed in the complex way of dealing the appropriate coefficients and solutions of the fuzzy systems.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Computational Mathematics Control Engineering
Identifiers
urn:nbn:se:oru:diva-71800 (URN)
Conference
9th International Conference on Intelligent Systems, Madeira Island, Portugal, September 25-27, 2018
Available from: 2019-01-24 Created: 2019-01-24 Last updated: 2019-02-01Bibliographically approved
Razvarz, S., Jafari, R., Gegov, A., Yu, W. & Paul, S. (2018). Neural Network Approach to Solving Fully Fuzzy Nonlinear Systems. In: Terrell Harvey & Dallas Mullins (Ed.), Fuzzy Modeling and Control: Methods, Applications and Research (pp. 46-68). Nova Science Publishers, Inc.
Open this publication in new window or tab >>Neural Network Approach to Solving Fully Fuzzy Nonlinear Systems
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2018 (English)In: Fuzzy Modeling and Control: Methods, Applications and Research / [ed] Terrell Harvey & Dallas Mullins, Nova Science Publishers, Inc., 2018, p. 46-68Chapter in book (Refereed)
Abstract [en]

The value of fuzzy designs improves whenever a system cannot be validated in precise mathematical terminologies. In this book chapter, two types of neural networks are applied to obtain the approximate solutions of the fully fuzzy nonlinear system (FFNS). For obtaining the approximate solutions, a superior gradient descent algorithmis proposed in order to train the neural networks. Several examples are illustrated to disclosehigh precision as well as the effectiveness of the proposed methods. The MATLAB environment is utilized to generate the simulations.

Place, publisher, year, edition, pages
Nova Science Publishers, Inc., 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:oru:diva-71792 (URN)2-s2.0-85058558000 (Scopus ID)978-1-53613-414-8 (ISBN)
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-01-25Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-4720-0897

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