Research on a Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control
Pneumatic miniature robotic control system usually adopts PID (Proportion Integration Differentiation) control strategy at present. To cope with the limitations of the basic PID control strategy, an improved single neural network PID control strategy is put forward in this paper. The control strategy is a single neuron adaptive controller with adjusting weighting coefficient, the weighting coefficient is realized according to the Hebb learning rule with supervisory. Both simulation and experimental results indicate that steady state error of the system equal to zero in the step-response curve, this scheme is a feasible control method for the 3-dof pneumatic miniature robotic control system.
Paul P. Lin and Chunliang Zhang
W. Li and X. Y. Dai, "Research on a Pneumatic Miniature Robotic Control System Based on Improved Single Neural Network PID Control", Applied Mechanics and Materials, Vols. 105-107, pp. 2157-2161, 2012