In recent years, the development and utilization of China’s wind energy resources have been greatly developed, but the large-scale wind power grid connection has brought threats to the safe and ...stable operation of the power grid. In order to ensure the stability of the power grid, it is necessary to reduce wind power output fluctuation and improve the tracking accuracy of dispatch instructions. Therefore, based on the distributed model predictive control of wind farm active power distribution strategy, an ultra-short-term wind power hybrid deep learning predictive model is proposed. The prediction results of a wind farm in North China show that the hybrid neural network model can achieve high ultra-short-term wind power prediction accuracy and is suitable for active power control prediction models. A two-layer distributed model is proposed to predict the active power control architecture of wind farms by implementing the clustering process with the Crow Search Algorithm. The distributed model predictive control strategy is proposed in the upper layer, and the centralized model predictive control algorithm is adopted in the lower control structure and optimized. The results show that the dual-layer distributed model predictive control strategy can better track the active power distribution instructions, reduce output fluctuation and scheduling value changes, and enhance the robustness of active power regulation, which is suitable for active power online control in wind farms.
This paper develops an integration slidingmode controller (ISMC) for a full-bridge single-ended-primary-inductance converter (SEPIC) supplied to an inverter-fed AC motor drive. Configuration of the ...developed SEPIC-based system is that a full diode bridge connected AC-to-DC SEPIC converter with power factor correction (PFC) is built for stably supplying DC voltage to the inverter. Under this configuration, the ISMC is applied for voltage control of the SEPIC converter with PFC of the AC-side line. With the PFC, the energy efficiency measured from the AC power source to the inverter-fed AC drive can substantially be improved. To perform the proposed ISMC, a Simulink model consisting of the AC source, diode-bridge rectifier, SEPIC, voltage-type inverter, and induction motor drive was built in a computer. Simulation results from the built Simulink model are illustrated to demonstrate the validity of the proposed ISMC for applications.
In this paper, an indirect field-oriented induction motor drive with a rotor time-constant adaptation is presented. Since the deviated rotor time-constant of an induction motor makes the indirect ...field-orientation inaccurate, an adaptation mechanism is proposed to tune the rotor time-constant to establish a complete indirect field-oriented control for an induction motor drive. With the rotor time-constant adaptation, the indirect field-oriented control has the robustness property for decoupling torque and flux components. In order to further insure the robustness of the servo control, a novel variable-structure speed controller is proposed under the adaptive field-orientation operation. A novel sliding surface with an integral component for the variable structure speed controller is designed, and exponential convergence in speed-tracking control is obtained. Using the proposed variable-structure speed controller, the insensitivity for parameter uncertainty and disturbance load is provided. Finally, a simulation and experimental results are demonstrated.
An adaptive wavelet neural network (AWNN) control with hysteresis estimation is proposed in this study to improve the control performance of a piezo-positioning mechanism, which is always severely ...deteriorated due to hysteresis effect. First, the control system configuration of the piezo-positioning mechanism is introduced. Then, a new hysteretic model by integrating a modified hysteresis friction force function is proposed to represent the dynamics of the overall piezo-positioning mechanism. According to this developed dynamics, an AWNN controller with hysteresis estimation is proposed. In the proposed AWNN controller, a wavelet neural network (WNN) with accurate approximation capability is employed to approximate the part of the unknown function in the proposed dynamics of the piezo-positioning mechanism, and a robust compensator is proposed to confront the lumped uncertainty that comprises the inevitable approximation errors due to finite number of wavelet basis functions and disturbances, optimal parameter vectors, and higher order terms in Taylor series. Moreover, adaptive learning algorithms for the online learning of the parameters of the WNN are derived based on the Lyapunov stability theorem. Finally, the command tracking performance and the robustness to external load disturbance of the proposed AWNN control system are illustrated by some experimental results.
In this paper, a filtering-type sliding-mode control with a radial basis function network (FSCRBFN) for a two-axis motion control system, which consists of two permanent magnet linear synchronous ...motors (PMLSMs), is proposed. First, the dynamics of the single-axis motion system with a lumped uncertainty which contains parameter variations, external disturbances, cross-coupled interference and nonlinear friction force is derived. Next, a filtering-type sliding-mode control (FSC) is adopted for the two-axis motion control system to confront the lumped uncertainty. Then, to improve the control performance in contour tracking, the FSCRBFN control approach is developed. In the control approach, a radial basis function network (RBFN) is employed mainly to estimate the lumped uncertainty. Moreover, the proposed control approach is performed on a digital signal process (DSP)-based control system using TMS320C32. Finally, some experimental results are illustrated to show the validity of the proposed control approach.
This paper presents a filtered switching-type sliding-mode backstepping control (FSTSMBC) approach for precise trajectory tracking of a piezopositioning stage. First, a dynamics of a mechanical ...motion system with the dynamics of hysteresis is constructed to represent the motion dynamics of the piezopositioning stage. Then, to simply represent the hysteresis dynamics, an approximation function is developed. From the constructed dynamics with the approximated hysteresis function, the FSTSMBC approach for the trajectory tracking is developed. By using the FSTSMBC approach, the trajectory tracking system of the piezopositioning stage possesses the features of a high-precision tracking performance, robustness, and effective chattering reduction compared to the results of using the traditional sliding-mode control. Experimental results of the time responses from the computer-controlled one-dimensional piezopositioning stage are illustrated to show the validity of the proposed control approach for practical applications.
In order to eliminate the effect of parameter variation on field-oriented control for induction motor drive, an adaptation algorithm for tuning the rotor time-constant is proposed. Based on the ...adaptive observation of the rotor flux linkages, the rotor time-constant is adapted to obtain an exact indirect-field-oriented control (IFOC). In this proposed algorithm, a related function to the variation of the rotor time-constant is designed, then the accurate slip frequency needed for IFOC is obtained from this error function through a PI-type (proportional-integral) filter. Furthermore, a novel variable structure speed control with integral sliding surface is proposed under the adaptive field-oriented operation. By means of the variable structure speed control, the dynamics of motor speed have the property of an exponentially convergent rate. Using the proposed adaptive field-oriented control and the variable structure speed control, the IFOC is robust to the variation of the rotor time-constant and the speed control is insensitive to parameter uncertainty and load disturbance. Finally, some simulation and experimental results are presented to validate the effectiveness.
This paper develops the control system of a piezoelectric micropositioner with an optimal PID control approach. In the control system development, the piezoelectric micropositioner is actuated by a ...voltage amplifier which is implemented by a linear operational amplifier with a compensator cascaded and the optimal PID control approach for trajectory tracking is developed from an approximated second-order linear model of the piezoelectric micropositioner. To obtain the approximated second-order linear model, an algorithm performed in a computer is taken to automatically identify the continuous-time transfer function from Bode diagrams. From the second-order linear model, the PID controller whose parameter values are determined theoretically by an optimal linear quadratic regulation (LQR) method is developed. By using the optimal PID control approach to trajectory tracking of the piezoelectric micropositioner, the high-performance tracking responses can be obtained. Experimental results from the piezoelectric micropositioner with the optimal PID control are illustrated to show the validity of the proposed control method for practical applications.
Robust nonlinear torque control for induction motor drive Kuo-Kai Shyu; Hsin-Jang Shieh
Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH36066),
1997, Letnik:
1
Conference Proceeding
In this paper, the nonlinear sliding-mode control combining binary control approach for an input-output linearization based induction motor model is proposed to design the robust torque and flux ...controllers. With the proposed control, we can obtain the advantages of that: (1) the generated torque of the induction motor presents a completely linear variable, (2) the rotor flux amplitude can be accurately controlled, (3) the transient performance is substantially improved, and (4) the robustness with respect to matched and mismatched uncertainties is provided.
