Model‐based robust control design and experimental validation of collaborative industrial robot system with uncertainty
Shengchao Zhen, Meng Zhang, Xiaoli Liu, Ye‐Hwa Chen
Abstract
Abstract Based on the traditional PID control and robust control algorithm, a novel practical robust control method is designed for the 6‐DOF collaborative industrial robot with uncertainty. The proposed algorithm consists of a robust term and a model‐based PD control term, which we call MPDP controller. It is demonstrated by Lyapunov theoretical analysis that the algorithm is able to guarantee uniform boundedness and uniform ultimate boundedness of the system. Simulations and experiments show the good performance of MPDP control in a robot with smaller steady‐state tracking errors and better robustness compared to PID controllers.
Topics & Concepts
Robustness (evolution)Control theory (sociology)PID controllerRobust controlControl engineeringRobotEngineeringLyapunov functionControl systemComputer scienceControl (management)Artificial intelligenceTemperature controlNonlinear systemChemistryBiochemistryElectrical engineeringGeneQuantum mechanicsPhysicsAdvanced Control Systems OptimizationAdvanced Control Systems DesignIterative Learning Control Systems