nach oben

Microsystem Technologies

Erschienen in:

03.03.2018 | Technical Paper

Development of a microcontroller-based adaptive fuzzy controller for a two-wheeled self-balancing robot

verfasst von: The Anh Mai, D. N. Anisimov, Thai Son Dang, Van Nam Dinh

Erschienen in: Microsystem Technologies | Ausgabe 9/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In this paper, an intelligent system use an adaptation fuzzy controller using Mamdani algorithm modified by relation models for a two wheeled self balancing robot is developed. Hardware model of the robot and sensor signal processing are described. The signals from sensors are filtered by a discrete complementary filter. A mathematical model of the robot is derived based on Newtonian mechanics. The proposed control system comprises two loops for regulation of the pitch angle and tracking the desired position of the robot. The inner loop uses a PD controller for position tracking. The outer loop is designed with an adaptive fuzzy controller to regulate balancing of the robot. The proposed controllers are tested in simulations using the mathematical model. These controllers are also designed and implemented in the real time system using a STM32F4 DISCOVERY kit which is equipped with a 32-bit ARM7 microprocessor. Simulations and experimental results show advantages of the adaptation fuzzy controller. Using the adaptive fuzzy controller for stability of the robot will allow a more effective and robust control to be implemented.

Vorheriger Artikel Highly stretchable thermal interface materials with uniformly dispersed network of exfoliated graphite nanoplatelets via ball milled processing route

Nächster Artikel Plasmonic op-amp circuit model using the inline successive microring pumping technique

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Abdulrahman A, Emhemed A (2013) Fuzzy control for nonlinear ball and beam system. Int J Fuzzy Log Syst 3(1):25–32CrossRef

Anisimov DN, Anh MT (2017) Dynamic properties of the fuzzy control systems based on the relational models. Mekhatronika Avtom Upr 18(5):298–307. https://doi.org/10.17587/mau.18.298-307 (in Russian) CrossRef

Anisimov DN, Vershinin DV, Kolosov OS, Zueva MV, Tsapenko IV (2013) Diagnosis of the current state of dynamic objects and systems with complex structures by fuzzy logic using simulation models. Sci Tech Inf Process 40(6):365–374 (in Russian) CrossRef

Anisimov DN, Dang TS, Banerjee S, Mai TA (2017) Design and implementation of fuzzy-PD controller based on relation models: a cross-entropy optimization approach. Eur Phys J Spec Top 226(10):2393–2406CrossRef

Campion G, Chung W (2008) Wheeled robots. In: Siciliano B, Khatib O (eds) Springer handbook of robotics, Chap 17. Springer, Berlin, pp 391–410CrossRef

Deepak BBVL, Parhi DR (2011) Kinematic analysis of wheeled mobile robot. Autom Syst Eng 5(2):96–111

Dote Y, Ovaska SJ (2001) Industrial applications of soft computing: a review. Proc IEEE 89(9):1243–1265CrossRef

Erbatur K, Kaynak O, Sabanovic A, Rudas I (1996) Fuzzy adaptive sliding mode control of a direct drive robot. Robot Auton Syst 19(2):215–227CrossRef

Fallahpour M, Fatehi A, Araabi BN, Azizi M (2007) A supervisory fuzzy control of back-end temperature of rotary cement kilns. In: International Conference on Control, Automation and Systems, Seoul, pp 429–434. https://doi.org/10.1109/ICCAS.2007.4406944

Filipescu A, Minzu V, Dumitrascu B, Filipescu A, Minca E (2011) Trajectory-tracking and discrete-time sliding-mode control of wheeled mobile robots. In: 2011 IEEE International Conference on Information and Automation, Shenzhen, pp 27–32. https://doi.org/10.1109/ICINFA.2011.5948958

Goher KM, Fadlallah SO (2017) Bacterial foraging-optimized PID control of a two-wheeled machine with a two-directional handling mechanism. Robot Biomim 4(1):1–19CrossRef

Grasser F, D’arrigo A, Colombi S, Rufer AC (2002) JOE: a mobile, inverted pendulum. IEEE Trans Ind Electron 49:107–114CrossRef

Hagras HA (2004) A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans Fuzzy Syst 12(4):524–539CrossRef

Herrera F, Lozano M (1996) Adaptation of genetic algorithm parameters based on fuzzy logic controllers. Genet Algorithms Soft Comput 8:95–125

Jager R (1995) Fuzzy logic in control. Technische Universiteit Delft, Delft

Jetto L, Longhi S, Vitali D (1999) Localization of a wheeled mobile robot by sensor data fusion based on a fuzzy logic adapted Kalman filter. Control Eng Pract 7(6):763–771CrossRef

Kolosov OS, Anisimov DN, Khripkov DV (2015) Research of the multilevel fuzzy diagnostic systems with the use of stochastic models. Mekhatronika Avtom Upr 16(4):254–261. https://doi.org/10.17587/mau.16.254-261 (in Russian) CrossRef

Kolosov OS, Anisimov DN, Khripkov DV (2016) The formation of multi-level fuzzy diagnosing systems structure using stochastic models. Mekhatronika Avtom Upr 17(6):375–383. https://doi.org/10.17587/mau.17.375-383 (in Russian)

Lee H-J, Jung S (2009) Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system. In: 2009 IEEE International Conference on Industrial Technology, Gippsland, VIC, pp 1–6. https://doi.org/10.1109/ICIT.2009.4939502

Lin SC, Tsai CC, Huang HC (2009) Nonlinear adaptive sliding-mode control design for two-wheeled human transportation vehicle. In: 2009 IEEE International Conference on Systems, Man and Cybernetics, San Antonio, TX, pp 1965–1970. https://doi.org/10.1109/ICSMC.2009.5346583

Liu Y-C, Chan W-H, Chen Y-Q (1995) Automatic white balance for digital still camera. IEEE Trans Consum Electron 41(3):460–466CrossRef

Lucas C, Milasi RM, Araabi BN (2006) Intelligent modeling and control of washing machine using locally linear neuro-fuzzy (LLNF) modeling and modified brain emotional learning based intelligent controller (BELBIC). Asian J Control 8(4):393–400MathSciNetCrossRef

Mamdani EH (1977) Application of fuzzy logic to approximate reasoning using linguistic synthesis. In: IEEE Transactions on Computers, vol C-26, no 12, pp 1182–1191. https://doi.org/10.1109/TC.1977.1674779

Mohareri O, Dhaouadi R, Rad AB (2012) Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks. Neurocomputing 88:54–66CrossRef

Ooi RC (2003) Balancing a two-wheeled autonomous robot, vol 3. University of Western Australia, Perth

Passino KM, Yurkovich S, Reinfrank M (1998) Fuzzy control, vol 20. Addison-Wesley, Reading

Pathak K, Franch J, Agrawal SK (2005) Velocity and position control of a wheeled inverted pendulum by partial feedback linearization. IEEE Trans Robot 21:505–513CrossRef

Pedrycz W, Gomide F (1998) An introduction to fuzzy sets: analysis and design of complex adaptive systems. MIT Press, Cambridge, Massachusetts

Ren T, Chen T, Chen C (2008) Motion control for a two-wheeled vehicle using a self-tuning PID controller. Control Eng Pract 16:365–375CrossRef

Sun L, Gan J (2010) Researching of two-wheeled self-balancing robot base on LQR combined with PID. In: 2010 2nd International Workshop on Intelligent Systems and Applications, Wuhan, pp 1–5. https://doi.org/10.1109/IWISA.2010.5473610

Thao N, Nghi D, Phuc N (2010) A PID backstepping controller for two-wheeled self-balancing robot. IFOST 2010:1–6

Wang L-X (1999) A course in fuzzy systems. Prentice-Hall, New Jersey

Wang W, Yi J, Zhao D, Liu X (2005) Double layer sliding mode control for second-order underactuated mechanical system. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 295–300. https://doi.org/10.1109/IROS.2005.1545462

Wasif A, Raza D, Rasheed W, Farooq Z, Ali SQ (2013) Design and implementation of a two wheel self balancing robot with a two level adaptive control. In: Eighth International Conference on Digital Information Management (ICDIM 2013), Islamabad, pp 187–193. https://doi.org/10.1109/ICDIM.2013.6694021

Wu J, Liang Y, Wang Z (2011) A robust control method of two-wheeled self-balancing robot. In: Proceedings of 2011 6th International Forum on Strategic Technology, Harbin, Heilongjiang, pp 1031–1035. https://doi.org/10.1109/IFOST.2011.6021196

Xu C, Li M, Pan F (2011) The system design and LQR control of a two-wheels self-balancing mobile robot. In: 2011 International Conference on Electrical and Control Engineering, Yichang, pp 2786–2789. https://doi.org/10.1109/ICECENG.2011.6057680

Yau HT, Wang CC, Pai NS, Jang MJ (2009) Robust control method applied in self-balancing two-wheeled robot. In: 2009 Second International Symposium on Knowledge Acquisition and Modeling, Wuhan, pp 268–271. https://doi.org/10.1109/KAM.2009.234

Yong Q, Yanlong L, Xizhe Z, Ji L (2011) Balance control of two-wheeled self-balancing mobile robot based on TS fuzzy model. In: Proceedings of 2011 6th International Forum on Strategic Technology, Harbin, Heilongjiang, pp 406–409. https://doi.org/10.1109/IFOST.2011.6021051

Titel: Development of a microcontroller-based adaptive fuzzy controller for a two-wheeled self-balancing robot
verfasst von: The Anh Mai
D. N. Anisimov
Thai Son Dang
Van Nam Dinh
Publikationsdatum: 03.03.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Microsystem Technologies / Ausgabe 9/2018
Print ISSN: 0946-7076
Elektronische ISSN: 1432-1858
DOI: https://doi.org/10.1007/s00542-018-3825-2

Neuer Inhalt

Bildnachweise

VDI-Icon, Profil Icon, inhalt2, Springer Professional Modul/© Springer Fachmedien Wiesbaden GmbH, Nachhaltigkeitsaward Key Visual/© Cometis AG/Global ESG Monitor | Daniel Rupp | Generiert mit KI, Search Icon, Banner Hanser, Jonas Klose/© Pine Valley Capital GmbH, Carina Kießling von der Strategieberatung Roland Berger/© Monika Walther Fotografie | ATZ, Beijing Auto Show 2024: Deutsche Hersteller wollen angreifen./© EKH-Pictures / Generated with AI / Stock.adobe.com, Zeitschrift Wissensmanagement Cover, PatentFit-Logo/© Springer Fachmedien Wiesbaden GmbH, Zukunftswerkstatt Sales Excellence 2024/© AndreyPopov / Getty Images / iStock, 2023_Antrieb/© supervisuell, ATZ-Webinar: Prototypenfreie Entwicklung durch Offline- und Driver-in-the-Loop-HiL-Tests /© (c) VI-grade

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 9/2018

Design of MI fuzzy PID controller optimized by Modified Group Hunting Search algorithm for interconnected power system

Performance analysis of MEMS sensor for the detection of cholera and diarrhea

Improved isolation RF MEMS switch with post release ashing

Nafion coated flexible bismuth sensor for trace lead and cadmium determination

In-situ 3D micro-sensor model using embedded plasmonic island for biosensors

Design optimization of a rectangular wave micromixer (RWM) using Taguchi based grey relational analysis (GRA)

Neuer Inhalt

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.