Research Of Nonlinear Sliding Mode Control Based On Fuzzy Control And Neural Network

Since the sliding mode control appear, because it has appeared completely robustness so it gradually get people widely used. But its shortcomings can produce is chattering by sliding mode control, and it is inherent defect of sliding mode control. In order to solve the problem, the fuzzy control and neural network control and adaptive control and so on many kinds of intelligent control methods combining with sliding mode control, not only effectively resolve the traditional problems in sliding mode control, but also inherited the inherent advantages of sliding mode control. This paper, the major work is as follows: First, this paper briefly reviews the development history of sliding mode control, research status and the basic principle by the reading at home and abroad on the basis of reference.Secondly, for a class of nonlinear systems, we constitutes the adaptive sliding mode control, basing on fuzzy control and adaptive control and combining sliding mode control. The control rules can through the control law on-line automatic adjustment. To eliminate chattering, we adopt the method reducing switch gain by using the fuzzy rules for the switch gain effective estimate. and the stability of the guarantee algorithm is prove by the lyapunov stability theorem.Once more, For a class of nonlinear system, presents a neural network adaptive sliding mode control. By using the neural network approximation control system of unknown nonlinear function, and the network weights through adaptive law, realize the online adjustment of tracking system error gradual towards zero. Considering the uncertain factors, it is difficult to measure the upper bound of uncertain factors, neural network was adopted to study uncertain factors, and the upper bound of the adaptive algorithm by interpreting value, and ensures the stability of the system, and reduced the chattering.Finally, good real-time performance by sliding mode control system, simple calculation, no overshoot and external disturbance of system parameters and has very strong robustness etc, it is very suitable for robot control. This paper first studied sliding mode control in the control robotic tracking, analyzes the control system stability and anti-jamming. Then using adaptive fuzzy system, through to the sliding mode control switch gain in adaptive approximation, eliminate chattering. And indicates the control strategy is effective through the simulation of manipulator.