National Science Foundationof China (51175494, 61128008), China Postdoctoral ScienceFoundation Funded Project (Grant No.2013M530954), theState Key Laboratory of Robotics Foundation (GrantNo.O8A120S, 2012017), Program for Liaoning Excellent Talentsin University (Grant No.LJQ2014021), Liaoning Province NaturalScience Fund Project(Grant No.2014020093), and Shenyang LigongUniversity Computer Application Key Discipline Foundation(Grant No.47710 04kfx09), Macao Science and TechnologyDevelopment Fund (108/ 2012/A3, 110/2013/A3), ResearchCommittee of University of Macau (MYRG203(Y1-L4)-FST11-LYM, MYRG183(Y1-L3)FST 11-LYM).
Since the conventional impedance control method for a rover arm is not suitable for unconstructed environment with uncertainties, a fuzzy inference method which improves the impedance model dynamically is introduced to realize high-precision control. The fuzzy PD control algorithm which applies to the joint control of a rover arm is analyzed in this paper. With the two level control algorithms, a novel dual-layer fuzzy control framework is proposed, which can enhance the control performance significantly. In order to verify the validity and reliability of the designed algorithms, the robotic arm of the CAS rover is considered as an experimental platform. Kinematics and dynamics models of robotic arm are derived at first. Moreover, the fuzzy inference mechanism and implementation process of impedance model parameters are illustrated. Extensive simulations and experimental results show that the control accuracy and the force control of the system have been significantly improved with the proposed dual-layer fuzzy control architecture.