In this paper, we present a prescribed performance control framework for trajectory tracking in Euler-Lagrange systems with unknown dynamics and prescribed input constraints. The proposed approach enforces hard funnel constraints, meaning that the prescribed performance bounds must not be violated during operation. We derive feasibility conditions that guarantee the tracking error evolves within these predefined funnels while ensuring bounded control inputs. To handle situations where the feasibility conditions are not satisfied, we introduce two approximation-free control strategies: one that actively drives the error back toward the funnel and another that prioritizes safety by preventing further deviation. The effectiveness and robustness of the proposed method are demonstrated through simulation studies and hardware experiments, highlighting its suitability for real-world robotic systems operating under strict input limits.

翻译：本文针对动力学未知且具有预设输入约束的欧拉-拉格朗日系统，提出了一种用于轨迹跟踪的预设性能控制框架。所提方法强制执行硬漏斗约束，这意味着在运行过程中不得违反预设的性能边界。我们推导了可行性条件，以保证跟踪误差在这些预定义的漏斗内演化，同时确保控制输入有界。为了处理可行性条件不满足的情况，我们引入了两种无需近似的控制策略：一种主动将误差驱动回漏斗内，另一种则通过防止进一步偏离来优先保障安全性。通过仿真研究和硬件实验，验证了所提方法的有效性和鲁棒性，突显了其在严格输入限制下运行的实际机器人系统中的适用性。