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Control of an omnidirectional spherical mobile robot using an adaptive Mamdani-type fuzzy control strategy

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Abstract

In this study, a supervisory control system with an adaptive Mamdani-type fuzzy controller (AMFC) is used to control an omnidirectional spherical mobile robot (ODSMR). The system combines an adaptive Mamdani-type fuzzy controller and a supervisory controller for ODSMRs with unknown external disturbances. Tracking is provided by a Mamdani-type fuzzy controller that approximates a theoretically exact control law, and a separate controller is used to cancel the residual of the approximation error. The control law is derived using Lyapunov stability theory to ensure the stability of the closed-loop system. Many external factors can cause the system to become unstable, so a supervisory controller is included. A decoupled control approach provides a simple method to achieve asymptotic stability for a fourth-order nonlinear system. The main concept of this approach is to decouple the system into two subsystems. Then, the primary subsystem combines the information provided by the secondary subsystem to generate a control that drives both subsystems to their desired states. This platform can move in any direction with no constraints. The efficiency of the proposed controller is verified with tests on an actual robot. The contributions of this study are: (1) the implementation of an ODSMR and (2) the application of the proposed AMFC with a supervisory control system to real-time control of the ODSMR.

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References

  1. Kwon S, Kim S, Yu J (2015) Tilting-type balancing mobile robot platform for enhancing lateral stability. IEEE/ASME Trans Mechatron 20(3):1470–1481

    Article  Google Scholar 

  2. Fukushima H, Muro K, Matsuno F (2015) Sliding-mode control for transformation to an inverted pendulum mode of a mobile robot with wheel-arms. IEEE Trans Ind Electron 62(7):4257–4266

    Article  Google Scholar 

  3. Huang J, Ri S, Liu L, Wang Y, Kim J, Pak G (2015) Nonlinear disturbance observer-based dynamic surface control of mobile wheeled inverted pendulum. IEEE Trans Control Syst Technol 23(6):2400–2407

    Article  Google Scholar 

  4. Yokoyama K, Takahashi M (2016) Dynamics-based nonlinear acceleration control with energy shaping for a mobile inverted pendulum with a slider mechanism. IEEE Trans Control Syst Technol 24(1):40–55

    Article  Google Scholar 

  5. Ye W, Li Z, Yang C, Sun J, Su CY, Lu R (2016) Vision-based human tracking control of a wheeled inverted pendulum robot. IEEE Trans Cybern 46(11):2423–2434

    Article  Google Scholar 

  6. Chiu CH, Tsai WR (2015) Design and implementation of an omnidirectional spherical mobile platform. IEEE Trans Ind Electron 62(3):1619–1628

    Article  Google Scholar 

  7. Han SI, Lee JM (2014) Fuzzy echo state neural networks and funnel dynamic surface control for prescribed performance of a nonlinear dynamic system. IEEE Trans Ind Electron 61(2):1099–1112

    Article  MathSciNet  Google Scholar 

  8. Kim DJ, Wang Z, Paperno N, Behal A (2014) System design and implementation of UCF-MANUS—an intelligent assistive robotic manipulator. IEEE/ASME Trans Mechatron 19(1):225–237

    Article  Google Scholar 

  9. Gao H, Fang J, Miao C (2014) Frequency-domain system identification of an unmanned helicopter based on an adaptive genetic algorithm. IEEE Trans Ind Electron 61(2):870–881

    Article  Google Scholar 

  10. Sharma N, Gregory CM, Johnson M, Dixon WE (2012) Closed-loop neural network-based NMES control for human limb tracking. IEEE Trans Neural Netw 30(3):712–725

    Google Scholar 

  11. Do KD (2014) Bounded assignment formation control of second-order dynamic agents. IEEE/ASME Trans Mechatron 19(2):477–489

    Article  Google Scholar 

  12. Li Y, Tong S, Li T (2015) Adaptive fuzzy output feedback dynamic surface control of interconnected nonlinear pure-feedback systems. IEEE Trans Cybern 45(1):138–149

    Article  Google Scholar 

  13. Li Y, Tong S, Li T (2015) Composite adaptive fuzzy output feedback control design for uncertain nonlinear strict-feedback systems with input saturation. IEEE Trans Cybern 45(10):2299–2308

    Article  Google Scholar 

  14. Li Y, Tong S, Li T (2016) Hybrid fuzzy adaptive output feedback control design for uncertain MIMO nonlinear systems with time-varying delays and input saturation. IEEE Trans Fuzzy Syst 24(4):841–853

    Article  Google Scholar 

  15. Liu Z, Wang F, Zhang Y, Cheng CLP (2016) Fuzzy adaptive quantized control for a class of stochastic nonlinear uncertain systems. IEEE Trans Cybern 46(2):524–534

    Article  Google Scholar 

  16. Huang CH, Wang WJ, Chiu CH (2011) Design and implementation of fuzzy control on a two-wheel inverted pendulum. IEEE Trans Ind Electron 58(7):2988–3001

    Article  Google Scholar 

  17. Chiu CH, Chang CC (2012) Design and development of Mamdani-like fuzzy control algorithm for a wheeled human conveyance vehicle control. IEEE Trans Ind Electron 59(12):4774–4783

    Article  Google Scholar 

  18. Druitt CM, Alici G (2014) Intelligent control of electroactive polymer actuators based on fuzzy and neurofuzzy methodologies. IEEE/ASME Trans Mechatron 19(6):1951–1962

    Article  Google Scholar 

  19. Lin CM, Li HY (2012) A novel adaptive wavelet fuzzy cerebellar model articulation control system design for voice coil motors. IEEE Trans Ind Electron 59(4):2024–2033

    Article  Google Scholar 

  20. Chaoui H, Sicard P (2012) Adaptive fuzzy logic control of permanent magnet synchronous machines with nonlinear friction. IEEE Trans Ind Electron 59(2):1123–1133

    Article  Google Scholar 

  21. Chiu CH (2010) The design and implementation of a wheeled inverted pendulum using an adaptive output recurrent cerebellar model articulation controller. IEEE Trans Ind Electron 57(5):1814–1822

    Article  Google Scholar 

  22. Wai RJ, Su KH (2006) Supervisory control for linear piezoelectric ceramic motor drive using genetic algorithm. IEEE Trans Ind Electron 53(2):657–673

    Article  Google Scholar 

  23. Roopaei M, Zolghadri M, Meshksar S (2009) Enhanced adaptive fuzzy sliding mode control for uncertain nonlinear systems. Commun Nonlinear Sci Numer Simulat 14:3670–3681

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Chih-Hui Chiu.

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Chiu, CH., Lin, CM. Control of an omnidirectional spherical mobile robot using an adaptive Mamdani-type fuzzy control strategy. Neural Comput & Applic 30, 1303–1315 (2018). https://doi.org/10.1007/s00521-016-2769-7

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  • DOI: https://doi.org/10.1007/s00521-016-2769-7

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