Tracking Control Based on Takagi-Sugeno Fuzzy Descriptor Model for Overhead Crane Combined With Input Shaping - Hoang-Phat Nguyen; Ngoc-Tam Bui; Thi-van-Anh Nguyen (IEEE Access, 2024)
Precise control of overhead crane systems, especially when there are disturbances, is crucial for ensuring safety and efficiency in operations. This paper addresses tracking control for overhead cranes that have variable cable lengths. It employs the Takagi-Sugeno (T-S) descriptor fuzzy method combined with Input Shaping (IS) techniques to significantly reduce payload oscillation. By representing the nonlinear system as local linear sub-models over different operating regions, the T-S descriptor fuzzy method effectively controls the crane system’s high nonlinearity. The Parallel Distributed Compensation (PDC) Integral controller is integrated into the design framework to enhance tracking control performance. Using Lyapunov theory, linear matrix inequalities (LMIs) are constructed, and the controller parameters are determined by solving these inequalities. By incorporating H-infinity or L-infinity performance criterion into the fuzzy model, robust controllers are developed to effectively reject disturbances and ensure tracking performance. Finally, simulations are conducted to evaluate the performance and effectiveness of the proposed controllers.