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Volatile organic compounds (VOCs) are typical pollutants with hazards for humans and the environment, which can be efficiently mitigated by catalytic combustion. Fe2O3‐based catalysts are a promising choice due to their low cost and strong redox ability. Several attempts have been made to promote the catalytic performance for Fe2O3‐based catalysts at low temperatures. This review summarizes the research progress on Fe2O3‐based catalysts for the oxidation of toluene, one of the most common and harmful VOC. Firstly, the structural properties and catalytic performances for Fe2O3‐based catalysts have been summarized, and the reaction mechanisms for toluene oxidation on the surface of Fe2O3‐based catalysts were detailed to comprehend the role of oxygen vacancies. Then, the modification for single Fe2O3 catalysts, including synthesis parameters, structure and morphology control, is introduced to reveal the correlation between physicochemical properties of catalysts and their activity for toluene oxidation. In addition, composite Fe2O3 catalysts, which can promote catalytic performance significantly by the synergetic effect between different components, were presented in detail. Moreover, waste‐derived Fe2O3 catalysts with sustainable merit as converting waste into worth have been discussed. Finally, the advanced machine learning tools, which are helpful in accelerating catalyst design, configuration optimization and reactivity prediction, have been introduced as an emerging research opportunity for the future. [ABSTRACT FROM AUTHOR]

Summary: An adaptive neural network (NN) command filtered backstepping control is proposed for the pure‐feedback system subjected to time‐varying output/stated constraints. By introducing a one‐to‐one nonlinear mapping, the obstacle caused by full stated constraints is conquered. The adaptive control law is constructed by command filtered backstepping technology and radial basis function NNs, where only one learning parameter needs to be updated online. The stability analysis via nonlinear small‐gain theorem shows that all the signals in closed‐loop system are semiglobal uniformly ultimately bounded. The simulation examples demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]