Rong-Fong Fung

Realization of a Motion Control IC for

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.

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In this paper, a control method combining the feedforward and feedback controllers is proposed to precisely control the dynamic performance of the piezoceramic actuator (PA). In the feedforward controller design, the hysteresis nonlinearity of the PA is modeled by using Preisach model first. Then a database of switching input/output values and a neural networks architecture treated as the inverse function of Preisach model are utilized in the feedforward controller In the feedback controller design, a PI controller is used to regulate the output error. Finally, some experimental results are validated the excellent tracking performances of the proposed controller.

Table Based on Novel FPGA Technology

This paper studies the linear and nonlinear, steady-state and dynamic behaviors of an optical beam deflector due to the electric input and temperature effect. The equations of motion incorporating the nonlinear deflections, electric and temperature effects are derived by the generic piezothermoelastic constitutive relations. The finite element method and convergent numerical integration scheme are used to simulate the thermoelastodynamic responses with uniform temperature rise. The nonlinear sensitivity analysis with respect to the temperature effect is performed for the maximum deviation angle. A simplified method for dynamic response and sensitivity analysis of the nonlinear system is proposed to save the computational time and avoid the complicated mathematics.

Precision Control of a Piezoceramic Actuator Using Neural Networks

This paper is to study the precision control of a piezoceramic actuator (PA). Due to the inherent hysteresis nonlinearity, the PA always causes position error in the open-loop system and instability in the closed-loop system. To remedy this problem, a new control method combining the feedforward and feedback controllers is proposed to improve the dynamic performance of the PA. In the feedforward controller design, the hysteresis nonlinearity of the PA is modeled by using Preisach model first. A database of input/output history and a neural networks architecture treated as the inverse function of Preisach model are also utilized in the feedforward controller. In the feedback controller design, a PI controller is used to regulate the error between the command input and system output. In experiment, the command of square wave, sinusoid wave and triangular wave is taken as the tested signal to validate the excellent performances of the proposed controller.