In four-motor servo systems, actuator failures influence control performance seriously through huge inertia ratio changes and unknown disturbances. To solve this problem, an adaptive fault-tolerant control scheme based on characteristic modeling and extended state observer is proposed. First, an adaptive sliding mode observer is designed as fault detection part and offers motor information for controller. Second, to simplify complex dynamic model, this servo system is described by a second-order difference equation. This model integrates uncertainties into three time–varying characteristic parameters to reflect system status. Third, a discrete-time extended state observer is applied to restrain system error caused by actuator failure. Then, a fault-tolerant controller is designed based on characteristic model, and its stability is guaranteed in the sense of Lyapunov stability theorem. These four parts make up the adaptive control scheme and its effectiveness in system control, and fault tolerant is evaluated by both simulation and experiment results.
Perez-PinalFJNunezCAlvarezR. Comparison of multi-motor synchronization techniques. In: 30th annual conference of IEEE industrial electronics society, IECON, Busan, 2–6 November 2004. New York: IEEE.
2.
HaiyanHULiningSMan-TianLI, et al. Multi-motor control system of a continuum robot for colonoscopy. Micromotors2011; 7(1): 839.
3.
WangXWuYZhangE, et al. Characteristic model-based adaptive controller with discrete extended state observer for servo systems. Proc IMechE, Part I: J Systems and Control Engineering2017; 231(4): 259–270.
4.
GaoZChengPQianM, et al. Active fault-tolerant control approach design for rigid spacecraft with multiple actuator faults. Proc IMechE, Part I: J Systems and Control Engineering2018; 232(10): 1365–1378.
5.
RotondoDNejjariFAkhielarabF, et al. Passive and active FTC comparison for polytopic LPV systems. In: European control conference (ECC), Zurich, 17–19 July 2013, pp.2951–2956. New York: IEEE.
6.
Del Carmen Rodriguez-LinanMHeathWP. Backlash compensation for plants with saturating actuators. Proc IMechE, Part I: J Systems and Control Engineering2017; 231(6): 471–480.
7.
WeiCYi-FeiWURen-HuiDU, et al. Fault diagnosis and fault tolerant control for the servo system driven by two motors synchronously. IET Control Theory Appl2014; 31(1): 27–34.
8.
MekkiHBenzinebOBoukhetalaD, et al. Fault tolerant control of PMSM drive using sliding mode strategy. In: 2015 Intl Aegean conference on electrical machines & power electronics (ACEMP), 2015 Intl conference on optimization of electrical & electronic equipment (OPTIM) & 2015 Intl symposium on advanced electromechanical motion systems (ELECTROMOTION), Side, 2–4 September 2015, pp.576–581.
9.
YeDYangGH. Adaptive fault-tolerant tracking control against actuator faults with application to flight control. IEEE Trans Control Syst Technol2006; 14(6): 1088–1096.
10.
DiaoYPassinoKM. Intelligent fault-tolerant control using adaptive and learning methods. Control Eng Pract2002; 10(8): 801–817.
11.
NouraHSauterDHamelinF, et al. Fault-tolerant control in dynamic systems: application to a winding machine. IEEE Control Syst Mag2000; 20(1): 33–49.
12.
ParkerLE. ALLIANCE: an architecture for fault tolerant, cooperative control of heterogeneous mobile robots. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems (IROS'94), vol. 2, Munich, 12–16 September 1994, pp.776–783. New York: IEEE.
13.
YinSLuoHDingSX. Real-time implementation of fault-tolerant control systems with performance optimization. IEEE Trans Ind Electron2013; 61(5): 2402–2411.
14.
PattonRJClarkRNFrankPM. Fault diagnosis in dynamic system, theory and applications. Ch Diagnos Syst Optimal Sens1989; 37: 821–828.
15.
JiangJ. Fault detection/diagnosis and controller reconfiguration in dynamic systems. IFAC Proc Vol1994; 27(5): 71–76.
16.
JiangJZhaoQ. Should we use parameter estimation or state estimation based FDI algorithms?IFAC Proc Vol1997; 30(18): 459–464.
17.
HamayunMTEdwardsCAlwiH. Integral sliding mode fault tolerant control incorporating on-line control allocation. In: International workshop on variable structure systems, Mexico City, 26–28 June 2010, pp.100–105. New York: IEEE.
18.
IchalalDMarxBRagotJ, et al. Observer based actuator fault tolerant control for nonlinear Takagi–Sugeno systems: an LMI approach. In: 18th Mediterranean conference on control and automation, MED'10, Marrakech, Morocco, 23–25 June 2010, pp.1278–1283. New York: IEEE.
19.
GaoZDingSX. Fault estimation and fault-tolerant control for descriptor systems via proportional multiple-integral and derivative observer design. IET Control Theory Appl2007; 1(5): 1208–1218.
20.
LiWJiangD. Robust H fault-tolerant control for networked control system based on Takagi-Sugeno fuzzy model. Intell Comput Syst2009; 25(4): 449–456.
21.
WuHHuJXieY. Characteristic model-based all-coefficient adaptive control method and its applications. IEEE Trans Syst Sci Cybern2007; 37(2): 213–221.
22.
WuHHuJXieY. Characteristic model-based intelligent adaptive control. Beijing, China: China Science and Technology Press, 2009.
23.
WangXWuYFZhangEZ, et al. Characteristic model-based adaptive controller with discrete extended state observer for servo systems. Proc IMechE, Part I: J Systems and Control Engineering2017; 231(4): 259–270.
24.
DingZWeiGDingX. Speed identification and control for permanent magnet synchronous motor via sliding mode approach. Syst Sci Control Eng Open Access2014; 2(1): 161–167.
25.
AttouAMassoumAChialiE. Sliding mode control of a permanent magnets synchronous machine. In: 4th international conference on power engineering, energy and electrical drives, Istanbul, 13–17 May 2013, pp.115–119. New York: IEEE.
26.
LascuCBoldeaIBlaabjergF. Super-twisting sliding mode control of torque and flux in permanent magnet synchronous machine drives. In: IECON 2013—39th annual conference of the IEEE industrial electronics society, Vienna, 10–13 November 2014, pp.3171–3176. New York: IEEE.
27.
WuYF. Research and implementation of a kind of servo systems driven by multi motors synchronously based on characteristic modeling. Nanjing University of Science & Technology Press, 2014, pp.67–72.
28.
XueH. Double-motor anti-backlash driving technology and its application in NC machine tool. Aeronaut Manuf Tech2009; 17: 84–91.
29.
Li-MingGJianL. Synchronization control of sheet feeding machine of shaft-less drives. Control Theory Appl2009; 26(5): 573–577.
30.
LuoXLiJ. Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase. Sci China Series F2011; 54: 448–459.
31.
GaoSGDongHRNingB. Characteristic model-based all-coefficient adaptive control for automatic train control systems. Sci China Series F2014; 57(9): 1–12.
XieJZhaoSShaZ, et al. Position servo control of the slider in double toggle mechanical press using Bezier curve model and fuzzy control. In: IEEE international conference on automation science and engineering, Trieste, 24–27 August 2011. New York: IEEE.
