Control of Mobile Robots Using Control Barrier Functions in Presence of Fault

This research proposes a multifaceted approach to mobile robot control and navigation. Firstly, a control Lyapunov function and control barrier function-based quadratic programing (CLF-CBF-QP) is introduced for nonholonomic mobile robots (NMR) to safely navigate around moving obstacles, addressing steering angle limitations and optimizing decay rates in real-time. In our study, we address the presence of actuator faults causing a loss of effectiveness in the nonholonomic mobile robot under consideration. Then, we develop a CLF-CBF-QP controller for mobile robots, using an extended Kalman filter (EKF) to estimate actuator loss of effectiveness gains and integrating them into the control system to mitigate actuator faults. Furthermore, simulations validate the method's effectiveness in overtaking and collision avoidance with moving obstacles.