| The study of humanoid robot is an advanced stage, which has great effects on the theory and practice. Humanoid arm is a very hot research topic as an important part of the humanoid robot. In this paper, serious research work has been done on a novel humanoid elbow, which is driven by linear motors, in which fuzzy identification modeling and fuzzy control method were employed.Firstly, in the light of the feature of the humanoid elbow and the property of the fuzzy systems, the model was acquired by fuzzy identification modeling method. And the simulation has been done on the humanoid elbow. Secondly, an adaptive fuzzy scheme for trajectory tracking was developed for humanoid elbow with parameter uncertainties and external disturbance. Within the scheme, a fuzzy logic system was employed to approximate the unknown robotic dynamics. Then, an adaptive fuzzy controller was obtained which combine with the adaptive methods so as to eliminate the system uncertainties and external disturbance. And the adaptive laws were obtained through stable control algorithms based on the Lyapunov stability theorem. Moreover, extra control term was designed to cancel the approximation errors, and the adjustable gains obtained from a Fuzzy Logic System were considered to receive the satisfying control effects. The proposed controller is robust to structured uncertainties and unstructured uncertainties. At last, a predictive control scheme was proposed, which constructed the fuzzy model of the plant using T-S fuzzy. The scheme predicted the future behavior of the output variables based on the fuzzy model, and the non-linear optimization problem was solved on line using a designed genetic algorithm, which had a number of advantages over conventional non-linear optimization techniques. This scheme coordinated the relations between the constraint condition and the control performances. The simulations were done based on the humanoid elbow, which show the validity of the control schemes in the paper. |
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