Adaptive fuzzy integral sliding mode pressure control for cutter feeding system of trench cutter

Abstract

A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system (CFS) of trench cutter (TC) in the presence of unknown external disturbances. The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition, the geological condition is time-varying. Due to the complex load characteristics of rock or soil, the feeding velocity of TC is related to geological conditions. What is worse, its dynamic model is subjected to uncertainties and its function is unknown. To deal with the particular characteristics of CFS, a novel adaptive fuzzy integral sliding mode control (AFISMC) was designed for feeding pressure control of CFS, which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller. The AFISMC feeding pressure controller is synthesized using the backstepping technique. The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system, integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory. Experiments are conducted on a TC test bench with the AFISMC under different operating conditions. The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ±0.3 MPa.

Keywords

electro-hydraulic system / cutter feeding system / feeding pressure control / adaptive fuzzy integral sliding mode control

References

[1] ZhouH, HouJ-y, ZhaoY-g, ChenY-long. Model-based trajectory tracking control for an electrohydraulic lifting system with valve compensation strategy [J]. Journal of Central South University, 2012, 19(11): 3110-3117

[2] SeoJ, VenugopalR, KennèJ. Feedback linearization based control of a rotational hydraulic drive [J]. Control Engineering Practice, 2007, 15(12): 1495-1507

[3] NiksefatN, SepehriN. Design and experimental evaluation of a robust force controller for an electro-hydraulic actuator via quantitative feedback theory [J]. Control Engineering Practice, 2000, 8(12): 1335-1345

[4] NamY, HongS K. Force control system design for aerodynamic load simulator [J]. Control Engineering Practice, 2002, 10(5): 549-558

[5] TruongD Q, AhnK K. Force control for hydraulic load simulator using self-tuning grey predictor-fuzzy PID [J]. Mechatronics, 2009, 19(2): 233-246

[6] GuanC, PanS-xia. Adaptive sliding mode control of electro-hydraulic system with nonlinear unknown parameters [J]. Control Engineering Practice, 2008, 16(11): 1275-1284

[7] LoukianovA G, SanchezE, LizaldeC. Force tracking neural block control for an electro-hydraulic actuator via secondorder sliding mode [J]. International Journal of Robust and Nonlinear Control, 2008, 18(3): 319-332

[8] AschemannH, SchindeleD. Sliding-mode control of a high-speed linear axis driven by pneumatic muscle actuators [J]. IEEE Transactions on Industrial Electronics, 2008, 55(11): 3855-3864

[9] LeeH, KimE, KangH J, ParkM. A new sliding-mode control with fuzzy boundary layer [J]. Fuzzy Sets and Systems, 2001, 120(1): 135-143

[10] CermanO, HušekP. Adaptive fuzzy sliding mode control for electro-hydraulic servo mechanism [J]. Expert Systems with Applications, 2012, 39(11): 10269-10277

[11] KomstaJ, van OijenN, AntoszkiewiczP. Integral sliding mode compensator for load pressure control of die-cushion cylinder drive [J]. Control Engineering Practice, 2013, 21(5): 708-718

[12] MohantyA, YaoBin. Indirect adaptive robust control of hydraulic manipulators with accurate parameter estimates [J]. IEEE Transactions on Control Systems Technology, 2011, 19(3): 567-575

[13] AlleyneA, LiuRui. A simplified approach to force control for electro-hydraulic systems [J]. Control Engineering Practice, 2000, 8(12): 1347-1356

[14] WangC-w, JiaoZ-x, WuS, ShangY-xing. Nonlinear adaptive torque control of electro-hydraulic load system with external active motion disturbance [J]. Mechatronics, 2014, 24(1): 32-40

[15] GuoK, WeiJ-h, TianQ-yan. Disturbance observer based position tracking of electro-hydraulic actuator [J]. Journal of Central South University, 2015, 22(6): 2158-2165

[16] KimW, ShinD, WonD, Choo ChungC. Disturbanceobserver- based position tracking controller in the presence of biased sinusoidal disturbance for electrohydraulic actuators [J]. IEEE Transactions on Control Systems Technology, 2013, 21(6): 2290-2298

[17] WeiJ-h, GuoK, TianQ-yan. Nonlinear supply pressure control for a variable displacement axial piston pump [J]. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2015, 29(7): 614-624

[18] LinJ, HuangZ Z. A hierarchical fuzzy approach to supervisory control of robot manipulators with oscillatory bases [J]. Mechatronics, 2007, 17(10): 589-600

[19] KalyoncuM, HaydimM. Mathematical modelling and fuzzy logic based position control of an electrohydraulic servosystem with internal leakage [J]. Mechatronics, 2009, 19(6): 847-858

[20] WangX-j, WangS-p, ZhaoPan. Adaptive fuzzy torque control of passive torque servo systems based on small gain theorem and input-to-state stability [J]. Chinese Journal of Aeronautics, 2012, 25(6): 906-916

[21] CermanO. Fuzzy model reference control with adaptation mechanism [J]. Expert Systems with Applications, 2013, 40(13): 5181-5187

[22] MerrittH EHydraulic Control Systems [M], 1967New YorkJohn Wiley & Sons Inc1-10