Design of a fuzzy fractional order adaptive impedance controller with integer order approximation for stable robotic contact force tracking in uncertain environment

• Autorzy: Cao Hongli

Identyfikatory

DOI

10.2478/ama-2022-0003

• Języki publikacji: EN

Abstrakty

EN

Current research in robot compliance control is unable to take both transient contact force overshoots and steady-state force tracking problems into account. To address this problem, we propose a fuzzy fractional order (FO) adaptive impedance controller to avoid the force overshoots in the contact stage while keeping force error in the dynamic tracking stage, where traditional control algorithms are not competent. A percentage gain is adopted to map FO parameters to integer order (IO) parameters by their natural properties, and a fuzzy logical controller is introduced to improve the system stability. The simulation results indicate that the proposed controller can be made more stable than and superior to the general impedance controller, and the force tracking results also have been compared with the previous control methods.

Słowa kluczowe

EN

adaptive impedance control; contact interactions; fractional order; fuzzy logic; integer order approximation

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Acta Mechanica et Automatica
• Rocznik: 2022
• Tom: Vol. 16, no. 1
• Strony: 16--26
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr.

Twórcy

autor

Cao Hongli

• Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China

• https://orcid.org/0000-0003-4324-3785

Bibliografia

• 1.Liang L, Chen Y, Liao L, Sun H, Liu YJR, Manufacturing C-I. A novel impedance control method of rubber unstacking robot dealing with unpredictable and time-variable adhesion force. 2021;67:102038.
• 2.Cao H, He Y, Chen X, Zhao XJIRtijorr, application. Smooth adaptive hybrid impedance control for robotic contact force tracking in dynamic environments. 2020.
• 3.Mokhtari M, Taghizadeh M, Mazare MJR. Hybrid adaptive robust control based on CPG and ZMP for a lower limb exoskeleton. 2021;39(2):181-99.
• 4.Dong Y, Ren T, Wu D, Chen KJJoI, Systems R. Compliance control for robot manipulation in contact with a varied environment based on a new joint torque controller. 2020;99(1):79-90.
• 5.Raibert MH, Craig JJ. Hybrid position/force control of manipulators. 1981.
• 6.Mason MTJIToS, Man,, Cybernetics. Compliance and force control for computer controlled manipulators. 1981;11(6):418-32.
• 7.Hogan N. Impedance control: An approach to manipulation: Part I—Theory. 1985.
• 8.Komati B, Pac MR, Ranatunga I, Clévy C, Popa DO, Lutz P, editors. Explicit force control vs impedance control for micromanipulation. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference; 2013: American Society of Mechanical Engineers.
• 9.Wu J, Ni F, Zhang Y,Fan S, Zhang Q, Lu J, et al. Smooth transition adaptive hybrid impedance control for connector assembly. 2018.
• 10.Akdoğan E, Aktan ME, Koru AT, Arslan MS, Atlıhan M, Kuran BJM. Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results. 2018;49:77-91.
• 11.Jung S, Hsia TC, Bonitz RGJIToCST. Force tracking impedance control of robot manipulators under unknown environment. 2004;12(3):474-83.
• 12.Duan J, Gan Y, Chen M, Dai XJR, Systems A. Adaptive variable impedance control for dynamic contact force tracking in uncertain environment. 2018;102:54-65.
• 13.Solanes JE, Gracia L, Muñoz-Benavent P, Esparza A, Miro JV, Tornero JJR, et al. Adaptive robust control and admittance control for contact-driven robotic surface conditioning. 2018;54:115-32.
• 14.Lu Z, Goldenberg AAJTIjorr. Robust impedance control and force regulation: Theory and experiments. 1995;14(3):225-54.
• 15.Fateh MM, Khorashadizadeh SJND. Robust control of electrically drivenrobots by adaptive fuzzy estimation of uncertainty. 2012;69(3):1465-77.
• 16.Li Y, Ge SS, Zhang Q, Lee THJICT, Applications. Neural networks impedance control of robots interacting with environments. 2013;7(11):1509-19.
• 17.Cao H, Chen X, He Y, Zhao XJIA. Dynamic adaptive hybrid impedance control for dynamic contact force tracking in uncertain environments. 2019;7:83162-74.
• 18.Xu WJJoDS, Measurement,, Control. Robotic time-varying force tracking in position-based impedance control. 2016;138(9):091008.
• 19.Sheng X, Zhang XJM. Fuzzy adaptive hybrid impedance control for mirror milling system. 2018;53:20-7.
• 20.Zhou Q, Li H, Shi PJIToFS. Decentralized adaptive fuzzy tracking control for robot finger dynamics. 2014;23(3):501-10.
• 21.Nikdel N, Badamchizadeh M, Azimirad V, Nazari MAJIToIE. Fractional-order adaptive backstepping control of robotic manipulators in the presence of model uncertainties and external disturbances. 2016;63(10):6249-56.
• 22.Zhong J, Li LJItocst. Tuning Fractional-Order ${PI}^{\lambda}{D}^{\mu} $ Controllers for a Solid-Core Magnetic Bearing System. 2015;23(4):1648-56.
• 23.Padula F, Visioli AJICT, Applications. Optimal tuning rules for proportional-integral-derivative and fractional-order proportional-integral-derivative controllers for integral and unstable processes. 2012;6(6):776-86.
• 24.Aguila-Camacho N, Duarte-Mermoud MAJIt. Fractional adaptive control for an automatic voltage regulator. 2013;52(6):807-15.
• 25.Shahri ESA, Alfi A, Machado JTJASC. Fractional fixed-structure H∞ controller design using augmented lagrangian particle swarm optimization with fractional order velocity. 2019;77:688-95.
• 26.Haji VH, Monje CAJAsc. Fractional order fuzzy-PID control of a combined cycle power plant using Particle Swarm Optimizationalgorithm with an improved dynamic parameters selection. 2017;58:256-64.
• 27.Efe MÖJIToII. Fractional order systems in industrial automation—a survey. 2011;7(4):582-91.
• 28.Ahmed S, Wang H, Tian YJAJoC. Robust adaptive fractional‐order terminal sliding mode control for lower‐limb exoskeleton. 2019;21(1):473-82.
• 29.Efe MÖJTotIoM, Control. Integral sliding mode control of a quadrotor with fractional order reaching dynamics. 2011;33(8):985-1003.
• 30.Feliu-Talegon D, Feliu-Batlle V, Tejado I, Vinagre BM, HosseinNia SHJIt. Stable force control and contact transition of a single link flexible robot using a fractional-order controller. 2019;89:139-57.
• 31.Muñoz-Vázquez AJ, Gaxiola F, Martínez-Reyes F, Manzo-Martínez AJAsc. A fuzzy fractional-order control of robotic manipulators with PID error manifolds. 2019;83:105646.
• 32.Oustaloup A, Levron F, Mathieu B, Nanot FMJIToC, Theory SIF, Applications. Frequency-band complex noninteger differentiator: characterization and synthesis. 2000;47(1):25-39.
• 33.Wang Y, Luo G, Gu L, Li XJJoV, Control. Fractional-order nonsingular terminal sliding mode control of hydraulic manipulators using time delay estimation. 2016;22(19):3998-4011.