This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies.

The efficiency and durability of a Proton Exchange Membrane Fuel Cell (PEMFC) can be improved with proper controller design to regulate the flow of reactants, cell stack temperature and humidity of the membrane. In this paper, sliding mode controllers (SMC) are proposed for a polymer electrolyte membrane fuel cell PEMFC. In particular, first order SMC and second order SMC based on super twisting algorithm are designed and investigated. The actual process has been formulated in simulation by Pukurushpan’s ninth order model. Performance of both control laws has been compared in simulation in MATLAB/Simulink environment in terms of oxygen excess ratio, net power generated, stack voltage/power produced and compressor motor voltage. Simulation results dictate that second order SMC demonstrates superior performance in terms of set-point tracking and disturbance rejection. The designed controller makes the interaction of various subsystems in a smooth manner and consequently improves the overall efficiency of the system and prolongs the stack life of the fuel cells.

This research addresses the challenge of controlling the air delivery system of Proton Exchange Membrane Fuel Cells (PEMFC) to ensure smooth operation and prolong device lifespan. The study is based on PEMFC model developed by Pukrushpan et al. for the Ford P2000 fuel cell vehicle. The stack temperature has been incorporated in the state-space model to improve its accuracy. Robust non-linear control strategies are designed and compared, including first-order Sliding Mode Control (SMC), second-order SMC, Integral SMC (ISMC), and Fast Terminal Integral SMC (FTISMC) with Super Twisting Algorithm (STA). In addition, a Uniform Robust Exact Differentiator (URED) based observer is proposed for estimating supply manifold pressure, mitigating measurement noise effects by eliminating the need of its direct measurement. Moreover, a three-layered feedforward neural network (TLFFNN) using FTISMC has been employed to estimate the continuous part of the control, trained to enhance robustness against noise. Extensive software simulations are conducted to validate the effectiveness of the proposed controllers. The simulation results demonstrate superior performance in terms of closed-loop stability, tracking accuracy, and robustness against measurement noise and system uncertainties, confirming the capability of the proposed control strategies to achieve reliable and accurate PEMFC air supply control. The results demonstrate that the proposed observer and all the control approaches achieve stable operation. However, FTISMC exhibits fastest convergence, superior tracking accuracy, and greater robustness to parameter uncertainties, external disturbances, and measurement noise. The proposed framework, thus, contributes towards the development of efficient and environmentally sustainable fuel cell technologies. Future research avenues may explore ways to enhance PEMFC robustness using online NN methods.