Path-tracking of nonlinear dynamics and input–output delays for vehicle error system via compound H∞ TS-feedforward controller

• Published in: Journal of the Franklin Institute Vol. 362; no. 11; p. 107772
• Main Authors: Lai, Weilong, Ma, Tianjun, Pan, Juntao
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.07.2025
• Subjects: Compound H∞TS-feedforward controller; Input–output delays; LMI parameter adjustment method; Lyapunov–Krasovskii functional; Takagi–Sugeno (TS) fuzzy model; Vehicle error path-tracking dynamics; Input–output delays; Takagi–Sugeno (TS) fuzzy model; Vehicle error path-tracking dynamics; Lyapunov–Krasovskii functional; LMI parameter adjustment method; Compound H∞TS-feedforward controller
• ISSN: 0016-0032
• DOI: 10.1016/j.jfranklin.2025.107772

This article proposes a composite H∞ Takagi–Sugeno (TS) feedforward controller integrated with fuzzy nonlinearity to address the path-following control problem of autonomous vehicles subject to input–output delays. First, a vehicle–road system is formulated using the norm-bound method to rigorously characterize parameter uncertainties and geometric dynamic properties. Second, the TS fuzzy modeling framework is adopted to approximate the vehicle’s inherent nonlinear dynamics while preserving accuracy. A Lyapunov–Krasovskii functional with free-weighting matrices is then applied to mitigate combined input–output delays, enabling the design of a low-conservatism TS H∞ feedback controller. To counteract non-convergence arising from physical constraints in the expectation model, an adaptive TS compensation feedforward controller is introduced, enhancing system convergence. Furthermore, the proposed composite H∞ TS controller reduces the number of system rules, thereby lowering computational complexity. Finally, Carsim-Simulink co-simulation validates the controller’s effectiveness in diverse road scenarios under delayed conditions, demonstrating superior performance compared to existing methods. •A complex multi parameter TS vehicle–road system is established.•A compound H∞ TS-feedforward controller based on multi-fuzzy is proposed.•The TS L-K functional based on free-weighting matrices is proposed.•The parameter adjustment method is used to deal with nonlinear matrix inequalities.•A adaptive feedforward controller based on TS membership functions is proposed.