Tracking control for nonlinear systems with time-varying delay using the fuzzy preview repetitive control approach

被引：0
作者：
Li, Li [1 ,3 ]
Wu, Jiang [2 ]
Meng, Xiaohua [1 ,3 ]
机构：
[1] Hubei Univ Econ, Sch Stat & Math, Wuhan 430205, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Math & Phys, Beijing 100083, Peoples R China
[3] Hubei Univ Econ, Hubei Ctr Date & Anal, Wuhan 430205, Peoples R China
来源：
FUZZY SETS AND SYSTEMS | 2025年 / 512卷
关键词：
Fuzzy preview repetitive control; Repetitive control; Augmented error system; T -S fuzzy system; Output feedback control; Linear matrix inequality; H-INFINITY CONTROL; DESIGN; ROBOTS;
D O I：
10.1016/j.fss.2025.109378
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper investigates an innovative technology for fuzzy preview repetitive control (FPRC) in nonlinear systems with time-varying delay and uncertainties using the Takagi-Sugeno (T-S) fuzzy model. The proposed FPRC strategy considers time-changing delays and previewable, periodic target signals. The controller integrates a fuzzy output feedback controller, a fuzzy preview controller, and a repetitive controller to address the tracking control problem of periodic target signals. The research constructs a T-S fuzzy augmented error system using the error system method and state augmentation technique. Subsequetnly, the FPRC design challenge is transformed into a feedback stabilization problem of the augmented error system. Empolying fuzzy Lyapunov function and linear matrix inequality (LMI) techniques, the study derives sufficient conditions for the asymptotic stability of the augmented error system in the form of a set of LMIs, presenting the design method of the FPRC law. The validity of the results is demonstrated through numerical simulations.
引用
收藏
页数：16
相关论文
共 47 条
  • [1] He L., Jiang C., Zhang L., A delay decomposition method for uncertain T-S fuzzy systems with stochastic time-delay under switching event-triggered control, Commun. Nonlinear Sci. Numer. Simul., 142, (2025)
  • [2] Zhang P., Liu Y., Jiao S., Yang C., Observer-based non-fragile control for T-S fuzzy switched systems against cyber attacks: a double-layer PDT switching method, Appl. Math. Comput., 495, (2025)
  • [3] Bhuvaneshwari G., Prakash M., Rakkiyappan R., Manivannan A., Stability and stabilization analysis of T-S fuzzy systems with distributed time-delay using state-feedback control, Math. Comput. Simul., 205, pp. 778-793, (2023)
  • [4] Jiawei Y., Yonggang C., Lifeng M., Juanjuan Y., Event-triggered regional stabilization for T–S fuzzy systems subject to communication delays and actuator saturations, J. Franklin Inst. Eng. Appl. Math., 361, 4, (2024)
  • [5] Zare I., Setoodeh P., Asemani M.H., T-S fuzzy tracking control of nonlinear constrained time-delay systems using a reference-management approach, J. Franklin. Inst., 358, 18, pp. 9510-9541, (2021)
  • [6] Ardak K., Rakkiyappan R., Sampled-data output tracking control based on T–S fuzzy model for cancer-tumor-immune systems, Commun. Nonlinear Sci. Numer. Simul., 128, (2024)
  • [7] Muhammad Shamrooz A., Thirunavukkarasu R., Arunachalam C., Quanxin Z., Improved event-triggered-based output tracking for a class of delayed networked T-S fuzzy systems, Int. J. Fuzzy Syst., 26, 4, pp. 1247-1260, (2024)
  • [8] Xingjian S., Yabin G., Chengwei W., Output tracking control for a class of continuous-time T–S fuzzy systems, Neurocomputing, 152, pp. 199-208, (2015)
  • [9] Xingyue L., Shengyuan X., Improved admissibility analysis for T-S fuzzy Markovian jump singular systems with time-varying delays, Fuzzy. Sets. Syst., 492, (2024)
  • [10] Yapeng L., Kun Z., Shouming Z., Kaibo S., Xuezhi L., Improved results for T-S fuzzy systems with two additive time-varying delays via an extended binary quadratic function negative-determination lemma, Fuzzy. Sets. Syst., 490, (2024)
12345