In order to quicken the response of the sliding mode control system, a novel reaching law with the dynamic coefficients, which could strengthen the role of the major term and weaken the role of the minor term respectively in the different stages, is proposed. The finite-time convergence of the improved reaching law is proved. The kinematical and the dynamics models of the automated guided vehicle are established, and a double closed-loop control is designed to perform the trajectory tracking. Sliding mode control method based on the improved reaching law is used to control the attitude of the automated guided vehicle, and the outer loop controller outputs the desired attitude. Simulation results show that the improved reaching law could make the system arrive at the sliding surface more rapidly than the conventional reaching laws, the automated guided vehicle could have faster attitude response speed, and the different given trajectories could be tracked effectively by the double closed-loop control method.

The deviation of the conveyor belt is a common failure that affects the safe operation of the belt conveyor. In this paper, a deviation detection method of the belt conveyor based on inspection robot and deep learning is proposed to detect the deviation at its any position. Firstly, the inspection robot captures the image and the region of interest (ROI) containing the conveyor belt edge and the exposed idler is extracted by the optimized MobileNet SSD (OM‐SSD). Secondly, Hough line transform algorithm is used to detect the conveyor belt edge, and an elliptical arc detection algorithm based on template matching is proposed to detect the idler outer edge. Finally, a geometric correction algorithm based on homography transformation is proposed to correct the coordinates of the detected edge points, and the deviation degree (DD) of the conveyor belt is estimated based on the corrected coordinates. The experimental results show that the proposed method can detect the deviation of the conveyor belt continuously with an RMSE of 3.7 mm, an MAE of 4.4 mm, and an average time consumption of 135.5 ms. It improves the monitoring range, detection accuracy, reliability, robustness, and real‐time performance of the deviation detection of the belt conveyor.

With the aim of solving warp tension control problems in the let-off system and opening system in the carbon fiber multilayer diagonal loom, dynamic models of warp tension are established in this study based on dynamic analysis. Adaptive fuzzy PID control is applied to the tension-networked control, and an adaptive fuzzy PID controller is designed to solve the problems of network induced delay, packet loss, and network bandwidth occupancy. A TrueTime simulation structure of the tension control system is also built. Compared with PID control, adaptive fuzzy PID control exhibited the advantages of a small overshoot, small fluctuation of output tension, good tracking effect, and stability in simulations under different conditions, including a 30-ms network induced delay, 10% packet loss, and 30% network bandwidth occupancy. The results of the simulations show that adaptive fuzzy PID control has better control effect than PID control, and is more suitable for tension-networked control systems in the carbon fiber multilayer diagonal loom.

In order to improve the control performance of the global sliding mode control method, a fast global sliding mode control method is proposed to accelerate the response of the system by changing the exponential decay function in the sliding surface as an exponential bilateral decay function which can make the dynamic sliding mode surface evolve into the linear sliding mode surface in the finite time. The exponential reaching law is used to design the control law, and Lyapunov stability theory is used to prove the stability of the system. The control method proposed in this article can be applied to control the uncertain nonlinear system. Simulation results show that the method has faster response rate than the conventional global sliding mode control method. The method can be used to control the quad-rotor unmanned helicopter, and its good practicability can be verified.

In order to overcome the disadvantage that the dynamic sliding mode surface of the discrete global sliding mode control has a too long evolution time, a quick discrete global sliding mode control method is proposed. A decay function of the dynamic sliding mode surface which can decay to zero in the finite time is constructed. Thereby, the dynamic sliding mode surface can evolve into the linear sliding mode surface at the given time. Thus, the method not only is strong global robustness, but also can quicken the response of the system and shorten the transition time. The method can be applied in the tension control system of the time delay carbon fiber multilayer diagonal loom. Simulation results prove the validity of the method.