Tracking Control for Two Link Robot Arm Using Neural Network with Simultaneous Perturbation Learning Rule

Neural networks are widely used for many fields including control problems. When we use a neural network as a controller, the direct inverse control scheme is the simplest approach. However, the scheme using the back-propagation method requires information, e.g. Jacobian, of an objective. If the objective is nonlinear, it will be difficult to know the information. Using the simultaneous perturbation learning rule, we can construct a neuro-controller, which is an inverse system of the objective or a proper controller, under the direct inverse control scheme without any information on the objective.In this paper, we report a tracking control for a two link robot arm using a neuro-controller with the simultaneous perturbation learning rule. Details of the proposed control scheme are described. Some simulation results and a result for a real two link robot arm show that the control scheme is feasible and useful.