Robust Event-triggered Fuzzy Energy-to-peak Disturbance Attenuation for Wheeled Mobile Robots

We explore the robust tracking problem for nonholonomic wheeled mobile robots (WMR) in the presence of uncertainties. The kinematics of the WMR are represented in the Takagi–Sugeno fuzzy form without modeling error. Recognizing the inherent challenge of obtaining a discrete-time model for time-triggered sampled-data controller design, we adopt an event-triggered sampled-data controller. The designed controller guarantees notable \(\mathcal {L}_{2}\) ${\mathcal{L}}_2$ – \(\mathcal {L}_{\infty }\) ${\mathcal{L}}_{\infty }$ disturbance attenuation performance and robustness against norm-bounded parametric uncertainties, excluding the Zeno phenomenon in the event triggering. Results of the case study about the WMR model demonstrate the efficacy of the proposed methodology.