A Intelligent Control Based On SA Algorithm And Its Application In Robot Control

The control problems of robotic manipulators have received great attention in theoretical and engineering for many years. When the robot model is exactly known, the technique of feedback linearization in nonlinear systems can solve the problem very well. However, the parameters of dynamic model of robotic manipulators may also be subject to change when the manipulator goes about its task. Meanwhile, the system can be influenced by uncertainties such as external disturbance and payload change. Therefore it is necessary to improve these existing control methods。This paper uses robot as researched object that is of strong coupling, nonlinear and multi-variable characters. A control system is proposed which consists of a fuzzy neural network controller. The parameters of the fuzzy neural network controller are optimized by the mixed learning methods with BP algorithm and Simulated Annealing algorithm which improves BP algorithm. The structure, principle and workflows of the system are given. The MATLAB simulation results show the feasibility and validity of the proposed method.