Search

The novel field-programmable-gate-array (FPGA) technology is able to combine an embedded processor and an application intellectual property to be a system-on-a-programmable-chip developing environment. Therefore, this paper presents a motion control IC for the X-Y table under this novel FPGA technology. The proposed motion control IC has two modules. One module performs the functions of the motion trajectory and two position/speed controllers for the X-Y table. The other module performs the functions of two current vector controllers of permanent-magnet synchronous motor drives. The former is implemented by software using a Nios II embedded processor due to the complicated control algorithm and low-sampling-frequency control (motion trajectory and position control: less than 1 kHz). The latter is implemented by hardware in the FPGA owing to the requirements of high-sampling-frequency control (current loop: 16 kHz; PWM circuit: 4-8 MHz) but simple computation. As a result, the hardware/software codesign technology can make the motion controller of the X-Y table more compact, flexible, perform better, and less costly. Index Terms--AC motor drives, field-programmable gate arrays (FPGAs), fuzzy control, motion control.

A robust fuzzy neural network (RFNN) control system is proposed in this study to control the position of the mover of a permanent magnet linear synchronous motor (PMLSM) drive system to track periodic reference trajectories. First, an ideal feedback linearization control law is designed based on the backstepping technique. Then, a fuzzy neural network (FNN) controller is designed to be the main tracking controller of the proposed RFNN control system to mimic an ideal feedback linearization control law, and a robust controller is proposed to confront the shortcoming of the FNN controller. Moreover. to relax the requirement for the bound of uncertainty term, which comprises a minimum approximation error, optimal parameter vectors and higher order terms in Taylor series, an adaptive bound estimation is investigated where a simple adaptive algorithm is utilized to estimate the bound of uncertainty. Furthermore, the simulated and experimental results due to periodic reference trajectories demonstrate that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties.

A new modified Reynolds equation for solving the ultrathing film gas lubrication is proposed to overcome the complicated and time-consuming difficulties of solving the linearized Boltzmann equation. The model equation is based on modified high-order slip-flow velocity distribution with three adjustable coefficients, which are corrected according to the Boltzmann model. The results are compared to those obtained using other kinds of currently employed modified Reynolds equations. It shows that the present model produces a closer approximation to that of the exact Boltzmann model than do other models, in a wider range of inverse Knudsen number. In addition, the newly derived equation is widely applicable to practical use.

A bimodal ultrasonic motor containing only one power amplifier and which makes use of two simultaneously excited modes to drive the rotor was described. The forced vibrations of the stator in contact with and without a rotor were investigated. The equations of motion that describes the vibrations and contact behavior were derived by Hamilton's principle and the geometry constraint. Some important factors, including structure design, exciting frequency, contact behavior and phase displacement were considered for bimodal ultrasonic motor design.