Multi Degree Of Freedom Robotic Arm Robust Control Technology Research

Robot is the product of technology in the 20th century. A large number of robots have emerged and been applied more and more widely, especially for industrial robot. The control strategies of mechanical arm have received great attention in theoretical research at all times.The development and the control theory of mechanical arm are introduced in this paper. Three kinds of arm's robust control theorys are designed: the torque control based on FNN(Fuzzy Neural Networks) controller, the computed torque control with sliding mode compensation and the computed torque control with WNN(Wavelet Neural Networks) compensation.FNN syncretizes the reasoning ability of fuzzy control and parameters' self-learning ability of neural networks. It does not depend on the precision of the mathematical model, and can overcome the impact of the uncertainty effectively. So FNN is regarded as the manipulator controller and used to the trajectory tracking of arm control.The computed torque control with sliding mode compensation is designed. The basic idea is that the arm system is decomposed as two parts: one is known system and the other is uncertainties system. Computed torque control is used to control the former part. For uncertainties system, sliding mode compensation control acts as the compensation.The computed torque control with WNN compensation is designed. To weaken the oscillation of sliding mode control, WNN is used instead of sliding mode control. Using of its approximation performance and self-learning ability, the uncertainties of the arm system can be compensated.A mechanical arm model with two-degrees freedom is simulated to prove the validity of the above control methods.Finally, the software system is constructured to the mechanical arm with six-degrees freedom, to provide a platform for the research of mechanical arm.