earticle

영어

This research paper focuses on the design and analysis of a high performance adaptive PD like fuzzy computed Torque controller for second order nonlinear uncertain (medical robot manipulator) system, in presence of uncertainties. The proposed approach effectively combines of design methods from Computed Torque controller (CTC), adaptive controller and fuzzy logic theory to improve the performance, stability and robustness of the CTC controller. Computed Torque Controller has two important challenges, system’s dynamic dependency and stability challenge. The nonlinearity term of the CTC is used to eliminate the decoupling and nonlinear term of link’s dynamic parameters. However, nonlinearity term of CTC is very essential to reliability but in uncertain condition or highly nonlinear dynamic systems, it can cause some problems. To solve this challenge the PD fuzzy logic controller is used as a model-based PD like fuzzy computed torque controller. The PD like fuzzy computed torque controller is updated based on online tuning coefficients. In order to reduce the online computation burden, the PD like fuzzy logic controller is also used to coefficients online tuning. As a result, in proposed method fuzzy logic controller is used to dynamic estimation and online tuning and as a result, improves the stability. This controller improves the stability and robustness, reduces the error as well and reduces the level of energy due to the torque performance as well.