P.-K. Huang

National Dong Hwa University, Chang-hua, Taiwan, Taiwan

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Publications (10)11.27 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: A sliding-mode controller (SMC) for a two-dimensional piezo-positioning stage is proposed. A mathematical model representing the motion dynamics of the stage is developed in which a hysteresis friction force describing the hysteresis behaviour of one-dimensional motion is used and a non-contant stiffness with the cross-coupling dynamics due to the effect of bending of lever mechanism in the x and y axes is also included. Based on the dynamic model, the proposed SMC with an asymptotic sliding surface is designed. A stability analysis is performed, and the transient performance is governed by the choice of control parameter values. With the proposed control scheme, the piezo-positioning stage is suitable for practical applications, especially in microscopy, with its need for validity of various trajectories. Experimental results show that the proposed controller provides high-performance dynamic characteristics and robustness to external load.
    IET Control Theory and Applications 08/2007; · 1.72 Impact Factor
  • H.-J. Shieh, P.-K. Huang
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    ABSTRACT: A filtering-type sliding-surface control (FTSSC) design with chattering alleviation compared to the traditional sliding-mode control (SMC) is proposed for precise trajectory tracking of a piezoelectric positioning stage (abbreviated by `piezo-stage'). First, considering the dynamics of motion of a mass-spring mechanical system, the differential equations of motion system which contains the parameters of a linear viscous friction, spring-coefficient, and a nonlinear hysteresis function - are proposed to describe the dynamics of motion of the piezo-stage. Then, the frequency-dependent hysteresis responses from both the proposed equations and the practical piezo-stage are illustrated to validate the equations. Based on the equations proposed, a state-space model is developed in which the applied voltage to the stage is defined as an output of a new control variable. According to the state-space model, the FTSSC design is proposed to provide not only the advantages of the traditional SMC, but also chattering improvement. Using the proposed control approach to the trajectory tracking of the piezo-stage, we can obtain that (a) high-performance tracking response, (b) robustness to system uncertainties and (c) chattering alleviation compared with the traditional SMC. Experimental results are illustrated to validate the proposed control approach for practical applications in trajectory tracking
    IET Control Theory and Applications 06/2007; · 1.72 Impact Factor
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    ABSTRACT: A frequency controlled three-phase induction generator (IG) system using ac-dc power converter is developed in this study. The electric frequency of the IG is controlled using the indirect field-oriented control mechanism. Moreover, an ac-dc power converter is adopted to convert the electric power generated by a three-phase IG from variable-frequency and variable-voltage to constant dc voltage. The rotor speed of the IG, the dc-link voltage and current of the power converter are detected simultaneously to yield maximum power output of the IG through dc-link power control. In this study, first, the indirect field-oriented mechanism is designed for the control of the IG. Then, a novel fuzzy modeling is developed to determine the flux control current and the maximum output power of the IG according to the rotor speed and the desired terminal voltage of the IG. Moreover, an online training recurrent fuzzy neural network (RFNN) with backpropagation algorithm is introduced as the tracking controller of dc-link power. Furthermore, some experimental results are provided to show the effectiveness of the proposed IG system using the RFNN controller for the dc-link power control. Finally, the control performance of the dc-link voltage control using the RFNN is also discussed by some experimental results
    IEEE Transactions on Power Electronics 02/2007; · 4.08 Impact Factor
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    F.J. Lin, P.K. Huang
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    ABSTRACT: A recurrent fuzzy neural network (RFNN) using genetic algorithm (GA) is proposed to control the mover of a linear induction motor (LIM) servo drive for periodic motion in this paper. First, the dynamic model of an indirect field-oriented LIM servo drive is derived. Then, an on-line training RFNN with backpropagation algorithm is introduced as the tracking controller. Moreover, to guarantee the global convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. In addition, a real-time GA is developed to search the optimal weights between the membership layer and the rule layer of RFNN on-line. The theoretical analyses for the proposed RFNN using GA controller are described in detail. Finally, experimental results show that the proposed controller provides high-performance dynamic characteristics and is robust with regard to plant parameter variations and external load disturbance
    Industrial Electronics and Applications, 2006 1ST IEEE Conference on; 06/2006
  • H. J. Shieh, P. K. Huang
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    ABSTRACT: In this study, an adaptive tracking control is proposed for trajectory tracking of a piezoelectric micropositioner which is often used to trajectory scanning applications in microscopy. To describe the dynamics of motion of a single-axis piezoelectric micropositioner approximately, a mathematical model composed of a linear differential equation about motion of mechanical systems and a specified hysteresis function is developed. Then, an adaptive tracking control based on this developed model is proposed. The main purpose of the linear differential equation is to describe the motion dynamics of the mechanical component and the specified hysteresis function is to emulate the hysteresis behaviour due to the stacked piezoelectric actuators built-in inside the micropositioner. To validate the proposed control approach, a PC-based control system which uses a laser interferometer as the displacement sensing detector is implemented. Experimental results illustrate the feasibility of the proposed controller for practical applications in trajectory tracking
    01/2006;
  • F.-J. Lin, D.-H. Wang, P.-K. Huang
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    ABSTRACT: A field-programmable gate array (FPGA)-based fuzzy sliding-mode controller, which combines both the merits of fuzzy control and sliding-mode control, is proposed to control the mover position of a linear induction motor (LIM) drive to compensate the uncertainties including the frictional force. First, the dynamic model of an indirect field-oriented LIM drive is derived. Next, a sliding-mode controller with an integral-operation switching surface is designed. The uncertainties are lumped in the sliding-mode controller, and the upper bound of the lumped uncertainty is necessary in the design of the sliding-mode controller. However, the upper bound of the lumped uncertainty is difficult to obtain in advance in practical applications. Therefore, a fuzzy sliding-mode controller is investigated, in which a simple fuzzy inference mechanism is utilised to estimate the upper bound of the lumped uncertainty. With the fuzzy sliding-mode controller, the mover of the LIM drive possesses the advantages of a good transient control performance and robustness to uncertainties in the tracking of periodic reference trajectories. A FPGA chip is adopted to implement the indirect field-oriented mechanism and the developed control algorithms for possible low-cost and high-performance industrial applications. The effectiveness of the proposed control scheme is verified by experimental results.
    IEE Proceedings - Electric Power Applications 10/2005; · 0.55 Impact Factor
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    ABSTRACT: An adaptive displacement tracking control using only displacement feedback is proposed for a piezo-positioning mechanism. In order to develop a dynamic model to represent the overall system dynamics of the controlled piezo-positioning mechanism, a specific function is proposed. This function that describes the hysteresis of the controlled mechanism contains information on the mechanical motion dynamics, hysteresis friction, disturbance load and parameter variations. Based on the developed model, an adaptive backstepping displacement tracking control is proposed, in which the backstepping adaptation of the specific function and the estimation of the reconstructed state with an unknown specific function are presented. The proposed control design leads to an improved tracking performance, and robustness to the external load-disturbance, and variations in system parameters. The validity of the proposed control design is demonstrated by experimental results.
    IEE Proceedings - Control Theory and Applications 10/2004; · 1.05 Impact Factor
  • F.J. Lin, R.J. Wai, P.K. Huang
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    ABSTRACT: A wavelet neural network (WNN) based two-axis motion control system using ultrasonic motor (USM) drives is proposed. First, a driving circuit for the USM, which is composed of a push-pull DC-DC power converter using PWM direct duty-cycle control and a current-source two-phase parallel-resonant capacitor-parallel load inverter, is introduced briefly. Moreover, since the dynamic characteristics of the proposed two-axis motion control system are complicated, an online trained WNN control scheme with varied learning rates is proposed to control the position of the two-axis moving table with high-performance features. In addition, a reference-word circular interpolator technique, which can permit the simultaneous operation of two-axis motion, is described. The effectiveness of the proposed motion control strategy is demonstrated by some experimental results.
    IEE Proceedings - Electric Power Applications 10/2004; · 0.55 Impact Factor
  • F.-J. Lin, C.-H. Lin, P.-K. Huang
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    ABSTRACT: A sliding-mode recurrent fuzzy neural network control (SMRFNNC) is proposed to control the mover of a permanent-magnet linear synchronous motor (PMLSM) servo drive so as to track a periodic sinusoidal reference trajectory. First, the PMLSM drive system is identified by a recurrent fuzzy neural network identifier (RFNNI) to provide sensitivity information of the drive system to a recurrent fuzzy neural network controller (RFNNC). Next, a sliding-mode adjuster (SMA) is determined according to the sliding mode condition. Then, the SMA is backpropagated through the RFNNI to train the parameters of the RFNNC online. Simulated and experimental results show that the control effort and chattering of the SMRFNNC are smaller than those of sliding-mode control. Moreover, a robust control performance is achieved when uncertainties occur including a nonlinear friction force.
    IEE Proceedings - Control Theory and Applications 08/2004; · 1.05 Impact Factor
  • F.-J. Lin, W.-D. Chou, P.-K. Huang
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    ABSTRACT: An adaptive sliding-mode controller based on real-time genetic algorithms (GAs) is developed for an induction motor (IM) servo drive. First, an adaptive sliding-mode controller with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilised to estimate the bound of uncertainties. Since the adaptation parameters for the above adaptive algorithm are constants, favorable response usually cannot be obtained due to the existence of uncertainties. Therefore, a real-time GA is developed to search the optimal adaptation parameters online. The position control for an IM servo drive using the proposed control strategy is illustrated. Simulated and experimental results show that the proposed controller provides high-performance dynamic characteristics and is robust with regard to plant parameter variations and external load disturbance.
    IEE Proceedings - Electric Power Applications 02/2003; · 0.55 Impact Factor