Adaptive B-spline-based fuzzy sliding-mode control for an auto-warehousing crane system

• The motivation of this research is conducting control system development for auto-warehousing crane which possesses the advantage of ease to implement.
• The main controller is a fuzzy-identification-based controller to track the auto-warehousing crane dynamics under various loading conditions along the x, y, and z directions.
• The proposed B-spline-based compensator provides the advantage of being undertaken by a microprocessor, where the function can be established in a recurrent way based on the given knot vector.
• The proposed ABFSM is applied to track the distance-speed reference trajectory of the auto-warehousing crane system. With the tuning law of the AFIC and the BCC, the stability can also be guaranteed by the means of Lyapunov function.
• In the simulation, the performance of the proposed ABFSM matches the specifications for motion control of crane with higher accuracy.

In this paper, an adaptive B-splined-based fuzzy sliding mode control (ABFSM) is presented to the application of auto-warehousing crane motion control. The ABFSM comprises an adaptive fuzzy identification controller (AFIC) and a B-spline-based compensation controller (BCC). The AFIC is designed to approximate the ideal controller of a crane system. To alleviate the load of fuzzy rule base construction, only the information from the sliding surface is used as the input of AFIC such that the conciseness and translucency of the control system can be upgraded. On the other hand, the BCC aims to compensate the approximation error of the AFIC. With the introduction of the B-spline function, the boundary of the approximation error can be represented by means of polynomial mapping. Thus, the design of the compensation controller can be achieved based on the characteristics of the B-spline function. In this paper, the objective of the ABFSM is to track the distance-speed reference trajectory of the crane control system. With the tuning law of the AFIC and the BCC, the stability can also be guaranteed by means of Lyapunov function. To validate the performance of the proposed approach, the ABFSM is applied to auto-warehousing crane motion control under various conditions for x, y, and z directions, respectively. From the simulation the advantages of the proposed ABFSM are demonstrated, where the capability to handle the uncertainty with efficiency is verified.

Figure optionsDownload as PowerPoint slideDistance–speed reference curve for k direction (k = x, y and z). The B-spline basis functions. (a) Premise and consequence parameters of the AFIC for x and z direction (b) Premise and consequence parameters of the AFIC for y direction. X-directional distance–speed control of the crane system (10 m, loaded). (a) Time–speed curve. (b) Distance–speed curve. (c) Error between crane speed and reference. (d) Time–force curve. (e) Distance–force curve.