An energy-efficient braking system that achieves high braking efficacy by utilising self-reinforcement is the Electronic Wedge Brake (EWB). Conversely, its vulnerability to fluctuations in the pad friction coefficient presents obstacles to the system’s stability and robustness. The purpose of this paper is to investigate the performance of Fuzzy Sliding mode control (FSMC) technqiue to estimate and compensate the variations in the pad friction coefficent and handle external disturbances. In addition, the system incorporates an Unscented Kalman Filter (UKF) to enhance the precision of the friction coefficient estimation, which allows for precise adaptive control adjustments. The control strategy proposed has been validated through extensive MATLAB/Simulink simulations, which have shown improved braking precision, enhanced robustness against friction coefficient variations, and superior performance in dynamic braking scenarios. The findings verify that the FSMC-based approach with UKF adaptation effectively mitigates the detrimental effects of friction variations, thereby enhancing the energy efficiency and stability of EWB systems.

Underwater control applications, such as control of Autonomous Underwater Vehicles (AUV)s, have recently gained significant interest, and there is a growing demand for high-speed wireless communication between AUVs and base station. Acoustic communication provides low data rates and high propagation delays, both of which are not suitable for employing high control gains for the navigation of AUVs. On the other hand, Radio Frequency (RF) communication provides high data rate, but it is constrained by high attenuation due to high conductivity and permittivity of water resulting in a short working range. In this work, we propose an underwater networked control system with acoustic and RF hybrid communication, where an acoustic link is employed for long range communication and RF link is applied in close range. Our performance results indicate that the acoustic and RF hybrid communication system takes up to 38.5% less time to dock, up to 91% smaller steady state error and spends up to 39% lower communication energy as compared to the acoustic only system at the expense of up to 22.35% higher motive energy.