Inverse Control of Cable-driven Parallel Mechanism Using Type-2 Fuzzy Neural Network

The level adjustment of cable-driven parallel mechanism is challenging due to the difficulty in obtaining an accurate mathematical model and the fact that different sources of uncertainties exist in the adjustment process. This paper presents a type-2 fuzzy neural network (T2FNN) based inverse control scheme for the level adjustment process. The T2FNN, whose consequent interval weights are trained by the iterative least squares estimation method, is used to approximate the inverse dynamics of the process and to handle uncertainties. Finally, the proposed control scheme and its counterpart — type-1 fuzzy neural network based inverse control scheme — are compared and implemented for leveling the cable-driven parallel mechanism.