Fuzzy Sliding Mode Constrained input Control for Robotic Manipulators Based on Systemic State

A novel fuzzy sliding mode controller for robotic manipulators is proposed. The use of a boundary layer in sliding-mode control has been a common technique to reduce chattering of the control input. However, different choices of the boundary layer width lead to conflicting effects. We apply fuzzy logic to adjusting the width of the boundary layer based on the state. The method can effectively eliminate chattering and ensure almost perfect control accuracy at the same time. However, the intelligent control strategies have high control input requirement, which confines the practical application of modern control strategies in large extent. So we add constrained input control strategies in the controller, and present fuzzy sliding mode constrained input controller based on systemic state. Simulations are given on a two-link robot in the end of paper, and the results show superior control performance than the conventional sliding mode controller for robot manipulators control