Alternating Positive and Negative Feedback Control Model Based on Catastrophe Theories

In automatic control systems, negative feedback has the advantage of maintaining a steady state, while positive can enhance some activities system. How to design controller with both modes is an interesting and challenging problem. Motivated by it, on basis idea catastrophe theories, taking as two different states system, adaptive alternating (APNF) model advantages proposed. By adaptively adjusting relevant parameters constructed symmetric function learning rule based error forward weight, be switched in form catastrophe. Through Lyapunov stability theory, convergence proposed APNF proven, which indicates that system guaranteed selecting appropriate parameters. Moreover, we present theoretical proof equivalent Finally, results simulation example show satisfactory performance response speed overshoot.