Guzey, Mehmet2026-03-262026-03-262021978303087725597830308772480302-97431611-334910.1007/978-3-030-87725-5_72-s2.0-85116430030https://doi.org/10.1007/978-3-030-87725-5_7https://hdl.handle.net/20.500.14901/1633In this paper, the design of adaptive regulation control of mobile robots in the presence of uncertain robot dynamics and with event-based feedback is presented. Two-layer neural networks (NN) are utilized to represent the uncertain nonlinear dynamics of the mobile robots, which is subsequently employed to generate the control torque with event-sampled measurement update. Relaxing the perfect velocity tracking assumption, control torque is designed to minimize the velocity tracking error, by explicitly taking into account the dynamics of the robot. The Lyapunov's stability method is utilized to develop an event-sampling condition and to demonstrate the regulation performance of the mobile robot. Finally, simulation results are presented to verify theoretical claims and to demonstrate the reduction in the computations with event-sampled control execution.eninfo:eu-repo/semantics/closedAccessEvent-Triggered ControlAdaptive ControlMobile RobotRobot DynamicsConference Object