Due to the tower cranes usually working in an outdoor environment, it is generally unavoidable for the obstacle to exist in the transportation path. Thus, it is critical for the tower crane systems to guarantee their safety and efficiency simultaneously. In this paper, for the 4DOF tower cranes, a novel adaptive tracking control approach is proposed by considering obstacle-avoidance trajectory planning. The state constraint equations are established firstly, by involving the auxiliary terms. And, the optimal time trajectory with physical constraints is obtained by the dichotomy method. Then, the fuzzy neural network is employed to handle the obstacle-avoidance trajectories generation problem under the different final positions and obstacle positions. An adaptive tracking control method with error constraints is further given to guarantee the precise tracking of the trolley and the jib. It is noteworthy that the proposed method not only constrains the state variables within predefined ranges but also constructs an improved trajectory planning method for the first time to avoid collisions. Additionally, the stability of the system is theoretically proven by the Lyapunov technique and LaSalle’s invariance principle. Finally, several experimental results demonstrate the superiority of the proposed method over comparative approaches in terms of effectiveness and robustness.

中文翻译：

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基于避障轨迹规划的跟踪误差约束四自由度塔式起重机自适应跟踪控制


由于塔式起重机通常在室外环境中工作，因此在运输路径中通常不可避免地存在障碍物。因此，塔式起重机系统同时保证其安全性和效率至关重要。针对四自由度塔式起重机，提出了一种考虑避障轨迹规划的新型自适应跟踪控制方法。首先，通过涉及辅助项来建立状态约束方程。并且，通过二分法获得具有物理约束的最佳时间轨迹。然后，采用模糊神经网络处理不同最终位置和障碍物位置下的避障轨迹生成问题;进一步给出了一种具有误差约束的自适应跟踪控制方法，以保证小车和副臂的精确跟踪。值得注意的是，所提方法不仅将状态变量约束在预定义范围内，而且首次构建了改进的轨迹规划方法以避免碰撞。此外，Lyapunov 技术和 LaSalle 不变性原理在理论上证明了系统的稳定性。最后，几个实验结果表明，所提出的方法在有效性和稳健性方面优于比较方法。