Study on Neural Immune PD Type Tracking Control for DC Actuating Mechanism
For control engineers working on DC actuating mechanisms, this is an incremental hybrid approach combining existing immune and neural methods.
This paper proposes a neural immune PD type tracking control method combining artificial immune control with neural networks for DC actuating mechanisms. Simulation results show the method follows desired trajectories more rapidly and accurately than previous methods, though no specific numerical improvements are provided.
Artificial Immune Systems(AIS) have been widely used in different fields, such as control, robotics, computer science and multi-agent systems. In this paper is proposed a new approach of neural immune PD type tracking control combining artificial immune control with neural network. It is assumed that the output of the helper T-cell is concerned with not only the error of system but also its changing rate, while the output of suppressor T-cell is unknown nonlinear function with respect to the amount and changing rate of antigens and the changing rate of antibodies, which is approximated by the output of neural network. From this, we derive neural immune PD type control law and apply it to the trajectory tracking of DC actuating mechanism. The validity of the proposed method is verified by simulation and the simulation results show that this method can follow the desired trajectory more rapidly and more accurately compared to the previous method.