Obstacle-avoidance trajectory planning based adaptive tracking control for 4DOF tower cranes with tracking error constraints

Abstract

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.