Human-simulated Intelligent Control Method Research Articles

Intelligent Vehicle Human-Simulated Steering Characteristics Access and Control Strategy

As the traditional control algorithm is over-dependent on accurate vehicle model in intelligent vehicle steering control, a human-simulated intelligent control method is proposed based on experienced driver steering characteristics. Intelligent vehicle unmanned steering system dynamics model and the driver model are set up. Through experienced drivers’ trial run experiment, the analysis is mainly conducted on the double lanes condition. After the transformation of coordinates on global positioning system (GPS) derivative, the path information of local coordinates is accessed. The ideal driver steering path is obtained through fuzzy C-means clustering algorithm. The human-simulated intelligent controller is designed. Characteristic model is established according to the ideal and practical steering angle deviation and the deviation rate. Besides, the corresponding control rules and control modality set are designed. The joint simulation under CarSim joint/Simulink environment shows that the humanoid steering controller designed in this paper has better tracking performance than the model predictive control.

Overview of human-simulated intelligent control method and its application

The current development of human-simulated intelligent control (HSIC) is introduced and the basic concepts, ideology and features are summarised. Then, examples are taken for the prototype algorithm of HSIC; the static characteristics, dynamic characteristics and stability of HSIC are analysed. The basic design steps of HSIC are further cleared. Finally, the application of HSIC in the trajectory tracking control for robot system is studied. In fact, HSIC is for choosing the appropriate control strategy according to the sign of the characteristic variables of the control system. The experimental results show that the HSIC method improves the control precision greatly.

Study on System Design and Control Methods of Polishing Robot System

A design method is presented for a polishing robot in unstructured working environment. Setting up a structure model of the polishing system, and the operation principle and control method are described. The human-simulated intelligent control method is applied to the control of contact force in unstructured environment, because of the uncertainty, variability and unstructured of the environment. The basic idea of the intelligent control method is based on the size of error and change direction of control variables. The conditions of the control rules and control decision are inferred by forward reasoning. The HSIC controlling function is achieved, which can strengthen people energy to revise and control the interaction force and position of the end-effector.