In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicle formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational burden. Initially, using the Taylor series concept, we derive the predictive models for the fixed-time sliding surface and reaching law. Subsequently, we formulate a constrained performance index by integrating these predictions with the control input. Ultimately, the optimal control input is computed through solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop fixed-time system stability in the presence of external disturbances and constraints. Furthermore, the comparative analysis with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, an experimental test is conducted to demonstrate the algorithm's potential for hardware implementation by employing the Hardware-in-the-Loop test.

中文翻译：

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基于预测器的多无人机编队飞行约束固定时间滑模控制

本文设计了一种基于预测器的固定时间滑模控制来解决多无人机编队飞行实现精确轨迹跟踪控制的问题。所提出的方法同时解决了各种实际需求，例如最优性、约束、固定时间收敛、外部干扰和计算负担。首先，利用泰勒级数的概念，我们推导了固定时间滑动面和趋近律的预测模型。随后，我们通过将这些预测与控制输入相结合来制定约束性能指数。最终，通过求解约束二次优化问题来计算最优控制输入。这项研究的一个突出特点是在存在外部干扰和约束的情况下闭环固定时间系统稳定性的理论保证。此外，与滑模预测控制律和固定时间滑模控制方法的比较分析表明，该方法实现了一种简单的控制方法，具有改进的性能和可接受的精度。最后，通过硬件在环测试来进行实验测试，以展示该算法在硬件实现方面的潜力。