The photovoltaic (PV) stand-alone system requires a battery charger for energy storage. This paper presents the modeling and controller design of the PV charger system implemented with the ...single-ended primary inductance converter (SEPIC). The designed SEPIC employs the peak-current-mode control with the current command generated from the input PV voltage regulating loop, where the voltage command is determined by both the PV module maximum power point tracking (MPPT) control loop and the battery charging loop. The control objective is to balance the power flow from the PV module to the battery and the load such that the PV power is utilized effectively and the battery is charged with three charging stages. This paper gives a detailed modeling of the SEPIC with the PV module input and peak-current-mode control first. Accordingly, the PV voltage controller, as well as the adaptive MPPT controller, is designed. An 80-W prototype system is built. The effectiveness of the proposed methods is proved with some simulation and experimental results.
This paper investigates precise trajectory tracking of a piezoactuator-driven stage with hysteresis behavior by using an approximator-based adaptive tracking control approach. Differential equations ...consisting of the dynamics of a linear motion system and a hysteresis function are first studied for describing the dynamics of motion of the piezoactuator-driven stage with hysteresis behavior. Then, a numerical optimization method is taken to identify the values of the parameters adopted in the differential equations. From the differential equations, an equivalent state-space model with an augmented integral input and with a defined hysteresis variable is established. Moreover, to approximate the unavailable hysteresis variable, an adaptive approximator that comprises a Gaussian radial-basis function network is adopted. Furthermore, from the state-space model, an adaptive approximator-based backstepping trajectory-tracking control is developed. Using the proposed control approach to trajectory tracking of the piezoactuator-driven stage, an improvement in transient performance and tracking errors, and robustness to the disturbance load, can be provided. Last, to show the validity of the proposed control approach, an implementation of the control algorithm on the computer-controlled single-axis piezoactuator-driven stage was developed. From the experimental results, the feasibility of the proposed control for practical applications can be confirmed.
In this paper, an integrator-backstepping-based dynamic surface control method for a two-axis piezoelectric micropositioning stage is proposed. First, according to the dynamics of motion of a ...mechanical mass-spring system, mathematical equations that contain a linear viscous friction, a varied elasticity with cross-coupling effect due to mechanical bending, and dynamics of a hysteresis variable is proposed to describe the motion dynamics of the two-axis piezopositioning stage. Next, from the equations, a state-space model in which the applied voltage to the stage is defined as an output of an integrator is derived. On the basis of this state-space model, the integrator-backstepping-based dynamic surface control is proposed. By using the proposed control method to trajectory tracking of the two-axis piezopositioning stage, the dynamic performance, robustness to parameter variations, and trajectory tracking error can be improved. Experimental results of the time responses from the computer-controlled two-axis piezopositioning stage illustrate the validity of the proposed control method for practical applications in trajectory tracking.
Because the control performance of a piezoactuator is always severely deteriorated due to hysteresis effect, an adaptive control with hysteresis estimation and compensation using recurrent fuzzy ...neural network (RFNN) is proposed in this study to improve the control performance of the piezo-actuator. A new hysteresis model by modifying and parameterizing the hysteresis friction model is proposed. Then, the overall dynamics of the piezo-actuator is completed by integrating the parameterized hysteresis model into a mechanical motion dynamics. Based on this developed dynamics, an adaptive control with hysteresis estimation and compensation is proposed. However, in the designed adaptive controller, the lumped uncertainty E is difficult to obtain in practical application. Therefore, a RFNN is adopted as an uncertainty observer in order to adapt the value of the lumped uncertainty E on line. And, some experimental results show that the proposed controller provides high-performance dynamic characteristics and is robust to the variations of system parameters and external load
To efficiently supply wide-range DC voltage from a pulse-width modulation (PWM) rectifier, this paper presents a single-phase, full-wave, diode-bridge, single-ended primary-inductor converter-type ...(SEPIC-type) power-factor-correction (PFC) rectifier in continuous conduction mode with a sliding surface-regulated current-mode PWM controller. According to the switched-mode operation of the rectifier, a fourth-order switch model of the SEPIC is derived. From the fourth-order model, a simplified state-averaged model which approximately describes the dynamic behaviors of both the output voltage and inductor current is proposed. Then, from the simplified state-averaged model, the sliding surface-regulated current-mode PWM controller for the SEPIC-type PFC rectifier is proposed. The sliding surface-regulated current-mode PWM controller comprises a sliding-mode voltage controller in outer loop for robust control of the output DC-voltage and a sliding-mode current controller in inner loop for phase-synchronized control of the inductor current. For experimental studies, implementation of the proposed control algorithm in a DSP controller and a laboratory prototype of the SEPIC-type rectifier with the DSP-based PWM controller were carried out. Experimental results from the DSP controller-applied SEPIC-type rectifier are illustrated to confirm the validity of the proposed controller for practical applications.
An adaptive displacement control with hysteresis modeling for a piezoactuated positioning mechanism is proposed in this paper because the dynamic performance of piezosystems is often severely ...deteriorated due to the hysteresis effect of piezoelectric elements. First, a new mathematical model based on the differential equation of a motion system with a parameterized hysteretic friction function is proposed to represent the dynamics of motion of the piezopositioning mechanism. As a result, the mathematical model describes a motion system with hysteresis behavior due to the hysteretic friction. Then, by using the developed mathematical model, the adaptive displacement tracking control with the adaptation algorithms of the parameterized hysteretic function and of an uncertain parameter is proposed. By using the proposed control approach on the displacement control of the piezopositioning mechanism, the advantages of the asymptotical stability in displacement tracking, high-performance displacement response, and robustness to the variations of system parameters and disturbance load can be provided. Finally, experimental results are illustrated to validate the proposed control approach for practical applications.
We propose a hybrid controller using a recurrent neural network (RNN) to control a levitated object in a magnetic levitation system. We describe a nonlinear dynamic model of the system and propose a ...computed force controller, based on feedback linearization, to control the position of the levitated object. To relax the requirement of the lumped uncertainty in the design of the computed force controller, an RNN functions as an uncertainty observer to adapt the lumped uncertainty on line. The computed force controller, the RNN uncertainty observer, and a compensated controller are embodied in a hybrid controller, which is based on Lyapunov stability. The computed force controller, with the RNN uncertainty observer, is the main tracking controller, and the compensated controller compensates the minimum approximation error of the RNN uncertainty observer. To ensure the convergence of the RNN, the adaptation law of the RNN is modified by using a projection algorithm. Experimental results illustrate the validity of the proposed control design for the magnetic levitation system.
An adaptive recurrent radial basis function network (ARRBFN) tracking controller for a two-dimensional piezo-positioning stage is proposed in this study. First, a mathematical model that represents ...the dynamics of the two-dimensional piezo-positioning stage is proposed. In this model, a hysteresis friction force that describes the hysteresis behavior of one-dimensional motion is used; and a nonconstant stiffness with the cross-coupling dynamic due to the effect of bending of a lever mechanism in x and y axes also is included. Then, according to the proposed mathematical model, an ARRBFN tracking controller is proposed. In the proposed ARRBFN control system, a recurrent radial basis function network (RRBFN) with accurate approximation capability is used to approximate an unknown dynamic function. The adaptive learning algorithms that can learn the parameters of the RRBFN on line are derived using Lyapunov stability theorem. Moreover, a robust compensator is proposed to confront the uncertainties, including approximation error, optimal parameter vectors, higher-order terms in Taylor series. To relax the requirement of the value of the lumped uncertainty in the robust compensator, an adaptive law is investigated to estimate the lumped uncertainty. Using the proposed control scheme, the position tracking performance is substantially improved and the robustness to uncertainties, including hysteresis friction force and cross-coupling stiffness, can be obtained as well. The tracking performance and the robustness to external load of the proposed ARRBFN control system are illustrated by some experimental results.
Trajectory tracking performance of a piezoelectric positioning stage almost depends on whether the tracking controller can effectively compensate the inherent hysteresis phenomenon. In this paper, a ...dynamic sliding-mode control (DSMC) with backstepping is proposed for the trajectory tracking of the piezoelectric positioning stage, which is suitable for a component of scanning microscopes. An equivalent model developed from a linear motion dynamics with addition of the hysteresis nonlinearity and strain-dependent function first is proposed to approximately represent the dynamics of motion of a one-dimensional piezoelectric positioning stage. Then, based on the equivalent model, the DSMC with an asymptotical sliding surface is proposed for the trajectory tracking control of the piezoelectric positioning stage. Moreover, the analysis of stability can be completed by mathematics, and the convergence rate of the tracking error can be governed by the choice of the control parameter values. Using the DSMC to trajectory tracking control, the piezoelectric positioning stage becomes more suitable for practical applications, especially with the need of various trajectories tracking in microscopy. To validate the proposed control scheme. a computer-based controller arid a piezoelectric positioning stage with a capacitive displacement sensor are implemented. Experimental results illustrate the feasibility of the proposed controller for trajectory tracking applications
In this paper, the nonlinear sliding-mode torque and flux control combined with the adaptive backstepping approach for an induction motor drive is proposed. Based on the state-coordinates transformed ...model representing the torque and flux magnitude dynamics, the nonlinear sliding-mode control is designed to track a linear reference model. Furthermore, the adaptive backstepping control approach is utilized to obtain the robustness for mismatched parameter uncertainties. With the proposed control of torque and flux amplitude, the controlled induction motor drive possesses the advantages of good transient performance and robustness to parametric uncertainties, and the transient dynamics of the induction motor drive can be regulated through the design of a linear reference model which has the desired dynamic behaviors for the drive system. Finally, some experimental results are demonstrated to validate the proposed controllers.
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