Intelligent Controller Emulating Human Control Abilities

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This project proposes a Human Simulating Intelligent Control (HSIC) theory which simulates human control abilities and enables effective control of a nonlinear system whose parameters are unknown or uncertain. A car-pendulum system moving on a restricted track and driven by a single motor is selected as a target system of the HSIC. At first, we investigated the mechanism of the former HSIC theory, it's performance and the difference between the HSIC theory and the other control methods by the computer simulation, then we confirmed that the HSIC theory shows high performance to simulate the manual control of human. Then, we employed a two-link arm system to develop a new HSIC theory. A human operator applies a torque to the second joint of the arm to controlled the position of the arm. The HSIC theory was revised by using the control output of the human operator. Finally, based on the proposed HSIC theory, the cart-pendulum system was designed and controlled. The whole control process consists of two steps : swinging-up and stabilizing. In swinging-up process, asymmetrical Bang-Bang control is employed to gather energy for the system. In stabilizing process, multi-variable PD control with positive feedback coordinating de-coupling is employed. The HSIC controller switches the control modes by means of online characteristic identifying. A real-time intelligent control system, which is designed based on our studies, successfully accomplished swing-up and stabilizing control of the car-pendulum system. The experiments prove that the control system is very stable even though the length of the pendulum varies or mass of it varies or the shape changes like "L". This project proves that the HSIC theory can effectively control the nonlinear, multi-variable and strong-coupling system such as swinging-up and stabilizing a cart-pendulum system without knowing its mathematical model.