This work develops a control strategy for unmanned systems, enhancing performance despite input limitations and actuator failures.
The event‐driven fixed‐time cooperative attitude controller for high‐speed unmanned system (HSUS) with input saturation and actuator failure is constructed in this article. Considering the limited system resources, the event‐triggered mechanism (ETM) is employed to reduce the frequency of controller updates. To better align with the actual situation, both input saturation and actuator failure are taken into account when designing the system controller. Subsequently, the radial basis function neural networks (RBF NNs) are implemented for efficiently approximating and handling unknown nonlinear relationships within the system. Furthermore, the fixed‐time convergence theorem is implemented to achieve improved transient performance. Ultimately, the effectiveness of the proposed control strategy is confirmed through a series of simulation examples.
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Ning et al. (2026) studied this question.
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