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Modern industrial manufacturing contains different kinds of surface modeling, which is processed by planar materials. For the principle of the most efficient materials using, how to optimize subdivision undevelopable surface before development becomes an important topic in CAM design and manufacturing industries. The paper transforms the basic parameters of surface before subdivision, and gives the standards of subdivision surfaces. We proved the feasibility and the existence of triangle subdivision algorithm. By introducing double parameters MÖbius transformation , the subdivision surface is more uniform. At last, numerical examples prove that the algorithm about the approximate development of the undevelopable surfaces is effective and practical.

In the industrial manufacturing process, most kinds of surfaces are processed by planar materials, but undevelopable surfaces are difficult develop to the plane. The approximation algorithms to develop a undevelopable surface is an important research topic in Computer Aided Geometric Design (CAGD). In this paper, we propose a new approximation algorithms based optimization algorithm. We guarantee the deformation vector make the minimum changes during the developing process. In the paper, some numerical example are given and the can illustrate the our method is effective.

With the fast developing about automobile electric technology, the advanced communication-network technology CAN-Bus is used in the designing of automobile instrument panel, and takes place of the traditional mechanical and electrical design. In this paper, a design of electronic automobile instrument has been introduced. The MCU is designed as a controller. In the design, traveled distance is displayed by LCD, revolving speed of wheels, running speed of car, water temperature and rest fuel amount is displayed by pointer driven by stepper motor. The automobile BUS-IP use two wires to communicate with the other CAN node, realize the resource using in common among the ECU. It has become the dominant technology in the future time. The content of thesis divides into hardware and software. CAN signal can be used to communicate between the power and driving system, use on-off circuit to control the automobile body information.

For nonlinear gas engine control system, uncertainty and complexity, this paper proposed electrical control design using artificial neural networks to improve the performance of electric and gas engines.

Trajectory tracking control is a major control problem in the application of the wheeled mobile robots (WMRs). However, many of the WMRs are autonomous which are equipped with several kinds of sensor to detect the position and orientation by itself, such as ultrasonic, laser, infrared and visual. This paper studies the implementation for a distributed network feedback control system and the trajectory tracking control algorithm for a non-autonomous WMR. The control system consists of a wireless sensor network (WSN) and a monitoring base station for measurement and feedback, and a non-autonomous WMR as controlled plant. To cope with the distributed and asynchronous measurements and slow response of the feedback channel, the sectional error amplitude limited algorithm is studied and the results show the system can effectively track a reference trajectory.

In many wireless sensor networks (WSNs), target tracking is an essential application. This paper studies the real-time target tracking algorithm and the implementation for a multi-target real-time tracking system. The system consists of a wireless sensor network which includes several distributed ultrasonic sensor nodes and a monitoring base station, and two robots as moving targets. To avoid the conflicts in the network, a sensor node task scheduling scheme, and an adaptive clustering and inter-cluster negotiation network protocol (ACICN) are proposed for the system. To cope with distributed and asynchronous measurements, data synchronization and Extended Kalman Filter (EKF) location algorithm are studied for the system. The experiments show that the system can effectively track multi targets simultaneously.