This study considers the control problem of constrained robotic manipulators with dynamic uncertainties. A new force/ position control strategy is proposed based upon terminal sliding mode and neural network. The terminal sliding mode combines position tracking with velocity tracking, and the neural network estimates unknown dynamics. Then, an adaptive control law is utilized to ensure finite-time convergent performance of position tracking and boundedness of contacting force tracking. Compared with existing force/position control strategies, the proposed strategy ensures the convergent performance without nominal model of the system dynamics. Simulation analysis verifies that the proposed strategy is effective.
Existing full-order terminal sliding mode (FOTSM) control methods often require a priori knowledge of the system model. To tackle this problem, two novel neural-network-based FOTSM control methods were proposed. The first one was model based but did not require knowledge of the uncertainties’ bounds. The second one was model free and did not require knowledge of the system model. Finite-time convergence of the two schemes was verified by theoretical analysis and simulation cases. Meanwhile, the designed methods avoided singularity as well as chattering.
With the rapid development of port logistics, it sets a higher request to the management level of the container terminal. In view of the terminal issues of the tedious process of manually collecting container and truck information with higher error rate, the management confusion and low utilization of container handling equipment, poor supervision of the terminal container goods as well as personnel, low degree of management information technology in terminal and so on, this article combines the radio frequency identification (RFID) technology to propose a container terminal management system based on the RFID technology and introduces the specific application of this management system in the port with emphasis. It can effectively solve the management issues in the contemporary container terminals so that the current situation of terminal management is improved.
To improve the speed of intelligent transformation of warehousing and logistics, a unilateral climbing shelf-type AGV in warehouse aisles is proposed. The modular design is adopted, and the crawling drive module, the cargo module, and the telescopic rotating arm are combined to form an AGV that can walk in all directions on the ground, climb, and traverse along the shelf track to complete the storage and retrieval operations. After the scheme is determined, 3D modeling is carried out through SliodWorks, performing static stress analysis on key stressed components. The kinematic model of the transition stage between ground and climbing is established by analytical method, and the kinematics simulation of the transition stage is completed in the SliodWorks Motion module. The results show that the movement speed curve of the cargo module is smooth, and there is no rigid impact. The Lagrangian dynamics equation is established for the transition process of AGV ground and climb, which provides a theoretical basis for control design. The overall structure of the AGV is reasonable, and the transition stage between the ground and the climb runs smoothly, meeting the design requirements.
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