Design And Application Of A Novel HSIC's Parameters Adjusting Level Strategy

In this paper, starting form the view of emulating human (control expert's) macrostructure and behavior functions, basing on the theory called Human Simulating Intelligent control (HSIC) and the method of analyzed phase-plane, the author proposes a new Human Simulating Intelligent control's method with its parameters that have the ability of self-leaning and self-tuning online. The self-tuning algorithm of the parameter adopts eigenvalue of the systemic error and derivative error and so on. Thus this method can overcome the disadvantage of the previous method which make the calibrating date not match up to the moveable track of the system, and improve the adaptability, rapidity and robustness of the Human Simulating Intelligent control's algorithm.This paper deals with swing-up and stabilizing control of the cart-doubled pendulum system. Under the guidance of intelligent analytical methods by decomposition of the control tasks and the intelligent decoupling strategies by the proper coordination among the complicated objectives (proposed by Chen QingChun), Following the Pose Adjusting Phase Method of the cart-doubled pendulum system(proposed by Zen Ji),The author clearly plot out the phases of pose adjusting and stabilization in the phase-plane , Using it instead of the previous control policy which plot out phases of pose adjusting and stabilization by simulative time. Then the parameters adjusting lever applied to stabilization phase of cart-double pendulum system, Improved its adaptability and robustness. At last the author pilot study mechanical self-learning of the cart-double pendulum systems, which make the process of converting cart-double pendulum system's state of failure into success.A series of the simulation results reveal that HSIC is really applicable for the nonlinear, multivariable and unstable mechanical system and attain satisfactory performance in return.