Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (1): 63-73.doi: 10.13229/j.cnki.jdxbgxb.20230331

Previous Articles     Next Articles

Prescribed finite-time tracking control with input buffer for a manipulator system

Peng SHEN1(),Xiao-hua LI2(),Hui LIU2   

  1. 1.School of Applied Technology,University of Science and Technology Liaoning,Anshan 114051,China
    2.School of Electronic and Information Engineering,University of Science and Technology Liaoning,Anshan 114051,China
  • Received:2023-04-10 Online:2025-01-01 Published:2025-03-28
  • Contact: Xiao-hua LI E-mail:sp-1981@163.com;lixiaohua6412@163.com

Abstract:

Facing the prescribed finite-time trajectory tracking control problem with input buffer for a linkage manipulator system,the backstepping method is used to design the prescribed finite-time trajectory tracking controller. A new prescribed finite-time performance function is proposed, which can more easily regulate control performance. With the help of this performance function, a constraint control law is designed for the tracking error, and a better transient performance than the existing prescribed finite-time performance function can be obtained under the same parameter conditions for the trajectory tracking process of the manipulator system. At the same time, a control input buffer function is designed, which solves both the overvoltage problem of control input caused by the overlarge position error of the manipulator and the problem that the manipulator system is difficult to start under heavy load. The simulation experiments verify the effectiveness and superiority of the proposed controller.

Key words: control engineering, buffer function, manipulator system, prescribed finite-time performance function, adaptive control, trajectory tracking control

CLC Number: 

  • TP273

Fig.1

Comparison between the old and new prescribed finite-time performance functions"

Fig.2

Linkage angle position y and desired trajectory yd"

Fig.3

Constraint performance curve of tracking error e1"

Fig.4

Trace tracking comparison between old and new prescribed performance functions"

Fig.5

Tracking error comparison between old and new prescribed performance functions"

Fig.6

Actual control input comparison between proposed method and the one in ref.[18]"

1 Cervantes I, Alvarez-Ramirez J. On the PID tracking control of robot manipulators[J]. Systems & Control Letters, 2001, 42(1): 37-46.
2 Ayala H V H, Dos Santos Coelho L D. Tuning of PID controller based on a multiobjective genetic algorithm applied to a robotic manipulator[J]. Expert Systems with Applications, 2012, 39(10): 8968-8974.
3 Meza J L, Santibáñez V, Soto R, et al. Fuzzy self-tuning PID semiglobal regulator for robot manipulators[J]. IEEE Transactions on Industrial Electronics, 2011, 59(6): 2709-2717.
4 吴爱国, 韩俊庆, 董娜. 基于极局部模型的机械臂自适应滑模控制[J]. 吉林大学学报: 工学版, 2020, 50(5): 1905-1912.
Wu Ai-guo, Han Jun-qing, Dong Na. Adaptive sliding mode control based on ultra⁃local model for robotic manipulator[J]. Journal of Jilin University (Engineering and Technology Edition), 2020, 50(5): 1905-1912.
5 Slotine J J E, Li W. On the adaptive control of robot manipulators[J]. The International Journal of Robotics Research, 1987, 6(3): 49-59.
6 Lee M J, Choi Y K.An adaptive neurocontroller using RBFN for robot manipulators[J]. IEEE Transactions on Industrial Electronics, 2004, 51(3): 711-717.
7 王伟, 赵健廷, 胡宽荣, 等. 基于快速非奇异终端滑模的机械臂轨迹跟踪方法[J]. 吉林大学学报: 工学版, 2020, 50(2): 464-471.
Wang Wei, Zhao Jian-ting, Hu Kuan-rong, et al. Trajectory tracking of robotic manipulators based on fast nonsingular terminal sliding mode[J]. Journal of Jilin University (Engineering and Technology Edition), 2020, 50(2): 464-471.
8 Su H, Qi W, Chen J, et al. Fuzzy approximation-based task-space control of robot manipulators with remote center of motion constraint[J]. IEEE Transactions on Fuzzy Systems, 2022, 30(6): 1564-1573.
9 Zhang S, Dong Y, Ouyang Y, et al. Adaptive neural control for robotic manipulators with output constraints and uncertainties[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(11): 5554-5564.
10 Izadbakhsh A, Khorashadizadeh S. Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator[J]. Journal of Robust and Nonlinear Control, 2020, 30(7): 2719-2735.
11 Yao W, Guo Y, Wu Y F, et al. Robust adaptive dynamic surface control of multi-link flexible joint manipulator with input saturation[J]. International Journal of Control, Automation and Systems, 2022, 20(2): 577-588.
12 Galicki M. Finite-time control of robotic manipulators[J]. Automatica, 2015, 51: 49-54.
13 Yang C, Jiang Y, Na J, et al. Finite-time convergence adaptive fuzzy control for dual-arm robot with unknown kinematics and dynamics[J]. IEEE Transactions on Fuzzy Systems, 2018, 27(3): 574-588.
14 Jia S, Shan J. Finite-time trajectory tracking control of space manipulator under actuator saturation[J]. IEEE Transactions on Industrial Electronics, 2019, 67(3): 2086-2096.
15 Doulgeri Z, Zoidi O. Prescribed performance regulation for robot manipulators[J]. IFAC Proceedings, 2009, 42(16): 573-578.
16 Guo Q, Zhang Y, Celler B G, et al. Neural adaptive backstepping control of a robotic manipulator with prescribed performance constraint[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 30(12): 3572-3583.
17 An S Y, Chen M, Wang H Q, et al. Fast finite-time dynamic surface tracking control of a single-joint manipulator system with prescribed performance[J]. International Journal of Systems Science, 2021, 52(8): 1551-1563.
18 Liu Y, Liu X P, Jing Y W. Adaptive neural networks finite-time tracking control for non-strict feedback systems via prescribed performance[J]. Information Sciences, 2018, 468: 29-46.
19 李小华, 胡利耀. 一类 p 规范型非线性系统预设性能有限时间 H 跟踪控制[J]. 自动化学报, 2021, 47(12): 2870-2880.
Li Xiao-hua, Hu Li-yao. Prescribed performance finite-time H tracking control for a class of p-normal form nonlinear systems[J]. Acta Automatica Sinica, 2021, 47(12): 2870-2880.
20 Keljik J J. Electricity 4: AC/DC Motors, Controls, and Maintenance[M]. New York:Cengage Learn, 2013.
21 Zhang J X, Yang G H. Robust adaptive fault-tolerant control for a class of unknown nonlinear systems[J]. IEEE Transactions on Industrial Electronics, 2017, 64(1): 585-594.
22 Tang Z L, Ge S S, Tee K P, et al. Adaptive neural control for an uncertain robotic manipulator with joint space constraints[J]. International Journal of Control, 2016, 89(7): 1428-1446.
23 李小华, 杨瑞芳, 刘辉, 等.一类机械臂系统自适应有限时间有界H跟踪控制[J]. 控制理论与应用, 2021, 38(1): 147-156.
Li Xiao-hua Yang Rui-fang, Liu Hui, et al. Adaptive finite-time bounded-H tracking control for a class of manipulator system[J]. Control Theory & Applications, 2021, 38(1): 147-156.
24 Zhang J X, Yang G H. Prescribed performance fault-tolerant control of uncertain nonlinear systems with unknown control directions[J]. IEEE Trans Autom Control, 2017, 62(12): 6529-6535.
25 Zhang J X, Yang G H.Robust adaptive fault-tolerant control for a class of unknown nonlinear systems[J]. IEEE Transactions on Industrial Electronics, 2017,64(1): 585-594.
26 Xing L, Wen C, Liu Z, et al. Event-triggered adaptive control for a class of uncertain nonlinear systems[J].IEEE Trans Autom Control, 2017,62(4): 2071-2076.
27 Xing L, Wen C, Liu Z, et al. Adaptive compensation for actuator failures with event-triggered input[J]. Automatica, 2017, 85: 129-136.
28 Huang Y, Liu Y. Practical tracking via adaptive event-triggered feedback for uncertain nonlinear systems[J]. IEEE Transactions on Automatic Control, 2019, 64(9): 3920-3927.
29 Kamali S, Tabatabaei S M, Arefi M M, et al. Prescribed performance quantized tracking control for a class of delayed switched nonlinear systems with actuator hysteresis using a filter-connected switched hysteretic quantizer[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 33(1): 61-74.
30 Liu H, Li X. A prescribed-performance-based adaptive finite-time tracking control scheme circumventing the dependence on the system initial condition[J]. Applied Mathematics and Computation, 2023, 448: No.127912.
[1] Yan-tao TIAN,Wen-yan YU,Yan-shi JI,bo XIE. Shared controller design for different driving behavior models [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(9): 2676-2686.
[2] Bin XIAN,Yin-xin WANG,Ling WANG. Distributed robust tracking control for multiple unmanned aerial vehicles: theory and experimental verification [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 2093-2103.
[3] Bin XIAN,Guang-yi WANG,Jia-ming CAI. Nonlinear robust control design for multi unmanned aerial vehicles suspended payload transportation system [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(6): 1788-1795.
[4] Hong-zhi WANG,Ting-ting WANG,Miao-miao LAN,Shuo XU. A novel sliding mode control strategy of multi-motor for robot arm based on position tracking [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1443-1458.
[5] Jun ZHAO,Zi-liang ZHAO,Qing-lin ZHU,Bin GUO. Output⁃feedback robust control of uncertain systems without observer [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(3): 828-835.
[6] Yan-an ZHANG,Yue-feng DU,Qing-feng MENG,Xiao-yu LI,Lei LIU,Zhong-xiang ZHU. Adaptive control of wet clutch pressure based on improved genetic algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(3): 852-864.
[7] Sheng-jie HOU,Zhong-lai WANG,Peng-peng ZHI,Hao ZHENG,Jing XU. Trajectory tracking control method of biplane air vehicle considering modelenvironment uncertainty [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(12): 3699-3710.
[8] Liu ZHANG,Qing-ming ZENG,Huan-yu ZHAO,Guo-wei FAN. Distributed adaptive vibration suppression control method of large solar panels for satellites based on Lyapunov theory [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(9): 2676-2685.
[9] Yan-min WANG,Wei-qi ZHANG,Guang-xin DUAN,Yang GE. Continuous non-singular terminal sliding mode control of electronic throttle [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(7): 2127-2135.
[10] Guo-yuan QI,Kuo LI,Kun WANG. Attitude constrained control of quadrotor unmanned aerial vehicle based on compensation function observer [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 853-862.
[11] Bo XIE,Rong GAO,Fu-qiang XU,Yan-tao TIAN. Stability control of human⁃vehicle shared steering system under low adhesion road conditions [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 713-725.
[12] Hong-yan GUO,Wen-ya YU,Jun LIU,Qi-kun DAI. Integrated moving horizon decision⁃making method for lane and speed of intelligent vehicle in complex scenarios [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 693-703.
[13] De-jun WANG,Kai-ran ZHANG,Peng XU,Tian-biao GU,Wen-ya YU. Speed planning and control under complex road conditions based on vehicle executive capability [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 643-652.
[14] Zhuo-jun XU,Yao-xiang WANG,Xing HUANG,Cheng PENG. Ground moving target search and location with multi⁃unmanned aerial vehicles [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 832-840.
[15] De-feng HE,Dan ZHOU,Jie LUO. Efficient cooperative predictive control of predecessor⁃following vehicle platoons with guaranteed string stability [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 726-734.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!