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Through the combination of experimental measurement and CFD (computational fluid dynamics) method, the fluid flow characteristics in the pipe of magnetic capsule robot for intestinal tract are studied. The PIV (particle imaging velocimetry) system is used to measure the fluid flow field around the magnetic-controlled capsule robot under certain translational and rotational speeds, and the rich flow field information (streamline, velocity, and vorticity) is obtained. At the same time, the CFD software is used to calculate the corresponding flow field and the force acting on the capsule robot, and the calculated value is basically consistent with the experimental value. The results show that, driven by the external permanent magnet, the magnetic capsule robot makes corresponding precession movement in the pipe filled with silicone oil, and the movement track is wavy. When the pipe diameter is increased, the fluid streamline around the capsule robot is more stable, the vorticity value is smaller, the resistance and resisting moment of the capsule robot in the forward direction become smaller. The PIV measurement method and CFD method used in this paper can be applied to the fluid flow field measurement and mechanical analysis of the smaller size capsule robot in the liquid environment.

Friction is inherent in mechanisms. In this paper a controller consisting of three schemes, proportional gain, pulse, and ramp (PPR), is proposed to achieve precise and fast pointing control under the presence of friction. Design of the PPR controller is based on two distinctive features of friction, the varying sticking force and presliding displacement of contacts. The latter is the main idea behind the ramp scheme to replace integration control, which induces slow dynamics in the sticking state. Simulation results demonstrate the robustness and effectiveness of the proposed controller.

Abrasive water jet is one of the advanced green machining tools and its advantages are well known. In order to obtain a product with high surface quality, the abrasive water jet machining process must be precisely controlled. Based on the artificial neural network, a model for the abrasive water jet cutting stainless steel process was built. The artificial neural network was then trained based on sample data set using improved BP algorithm. The trained network establishes nonlinear relationships among the parameters of abrasive water jet cutting process and cutting surface quality. Consequently the surface quality of the part can be indirectly controlled by adjusting the cutting speed of water jet. The satisfied results were obtained using the trained artificial neural network model through the check data set.

This paper analyzes the Direct Torque Control (DTC) theory. We find that dynamical and stable performance are not hold with traditional voltage switch strategy at the same time. It presents a new direct torque control method of brushless DC motor, and introduces a space voltage vector selection table. By the addition of zero vector in the converter control, traditional three order torque control loop translates to five order torque control loop. So torque output have good dynamical and stable response, and stable torque ripple of traditional DTC can be improved. The direct torque control for brushless DC motor is implemented with TI DSP TMS320LF2407A. The experiment results show that the system has very quick dynamic response, low torque ripple and high performance requirements of industrial applications.