The Experts below are selected from a list of 13152 Experts worldwide ranked by ideXlab platform
Rong-jong Wai - One of the best experts on this subject based on the ideXlab platform.
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intelligent control of induction Servo Motor drive via wavelet neural network
Electric Power Systems Research, 2002Co-Authors: Rong-jong Wai, Jiaming ChangAbstract:Abstract This study presents an intelligent control system for an induction Servo Motor drive to track periodic commands using a wavelet neural network (WNN). With the field orientation mechanism, the dynamic behavior of the induction Servo Motor drive system is rather similar to a linear system. However, the uncertainties, such as mechanical parametric variation, external disturbance, unstructured uncertainty due to nonideal field orientation in transient state, and unmodelled dynamics in practical applications influence the control performance. Therefore, an intelligent control system that is an on-line trained WNN controller with adaptive learning rates is proposed to control the rotor position of the induction Servo Motor drive. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary according to the powerful learning ability of the intelligent control system. With the proposed intelligent control system, the controlled induction Servo Motor drive possesses the advantages of good tracking control performance and robustness to uncertainties under wide operating ranges. The effectiveness of the proposed control scheme is verified by both simulated and experimental results.
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total sliding mode controller for pm synchronous Servo Motor drive using recurrent fuzzy neural network
IEEE Transactions on Industrial Electronics, 2001Co-Authors: Rong-jong WaiAbstract:In this paper, the dynamic responses of a recurrent-fuzzy-neural-network (RFNN) sliding-mode-controlled permanent-magnet (PM) synchronous Servo Motor are described. First, a newly designed total sliding-mode control system, which is insensitive to uncertainties, including parameter variations and external disturbance in the whole control process, is introduced. The total sliding-mode control comprises the baseline model design and the curbing controller design. In the baseline model design, a computed torque controller is designed to cancel the nonlinearity of the nominal plant. In the curbing controller design, an additional controller is designed using a new sliding surface to ensure the sliding motion through the entire state trajectory. Therefore, in the total sliding-mode control system, the controlled system has a total sliding motion without a reaching phase. Then, to overcome the two main problems with sliding-mode control, i.e., the assumption of known uncertainty bounds and the chattering phenomena in the control effort, an RFNN sliding-mode control system is investigated to control the PM synchronous Servo Motor. In the RFNN sliding-mode control system, an RFNN bound observer is utilized to adjust the uncertainty bounds in real time. To guarantee the convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. Simulated and experimental results due to periodic step and sinusoidal commands show that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties.
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a pm synchronous Servo Motor drive with an on line trained fuzzy neural network controller
IEEE Transactions on Energy Conversion, 1998Co-Authors: Faajeng Lin, Rong-jong Wai, Hongpong ChenAbstract:A permanent magnet (PM) synchronous Servo Motor drive with integral-proportional (IP) position controller and a proposed on-line trained fuzzy neural network (FNN) controller is introduced in this paper. First, an IP position controller is designed according to the estimated plant model to match the time-domain command tracking specifications. Then the resulting closed-loop tracking transfer function is used as the reference model, and an adaptive signal generated from the proposed FNN controller, whose membership functions and connective weights are trained on-line according to the model-following error of the states, is added to the control system to preserve a favorable model-following characteristics under various operating conditions.
Faajeng Lin - One of the best experts on this subject based on the ideXlab platform.
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variable structure adaptive control for pm synchronous Servo Motor drive
IEE Proceedings - Electric Power Applications, 1999Co-Authors: Faajeng Lin, Kuokai Shyu, Y S LinAbstract:A newly designed variable-structure controller for a permanent magnet (PM) synchronous Servo Motor drive, which is insensitive to uncertainties including parameter variations and external load disturbance, is introduced. To overcome the two main problems with variable-structure control, i.e. the assumption of known uncertainty bounds and chattering phenomena in the control effort, a variable-structure adaptive (VSA) controller is investigated. In the VSA controller a simple adaptive algorithm is utilised to estimate the uncertainty bounds; moreover, the chattering phenomenon is reduced. A variable-structure direct adaptive (VSDA) controller comprising the VSA control algorithm and a direct adaptation law is proposed to further improve the control performance of the variable-structure controller. The position control of a PM synchronous Servo Motor drive with the variable-structure control strategies is illustrated. Simulated and experimental results show that the developed controllers provide high-performance dynamic characteristics and are robust with regard to plant parameter variations and external load disturbance.
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a pm synchronous Servo Motor drive with an on line trained fuzzy neural network controller
IEEE Transactions on Energy Conversion, 1998Co-Authors: Faajeng Lin, Rong-jong Wai, Hongpong ChenAbstract:A permanent magnet (PM) synchronous Servo Motor drive with integral-proportional (IP) position controller and a proposed on-line trained fuzzy neural network (FNN) controller is introduced in this paper. First, an IP position controller is designed according to the estimated plant model to match the time-domain command tracking specifications. Then the resulting closed-loop tracking transfer function is used as the reference model, and an adaptive signal generated from the proposed FNN controller, whose membership functions and connective weights are trained on-line according to the model-following error of the states, is added to the control system to preserve a favorable model-following characteristics under various operating conditions.
Peter Maiser - One of the best experts on this subject based on the ideXlab platform.
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a novel power splitting drive train for variable speed wind power generators
Renewable Energy, 2003Co-Authors: Xueyong Zhao, Peter MaiserAbstract:In this paper a novel electrically controlled power splitting drive train for variable speed wind turbines is presented. A variable speed wind turbine has many advantages, mainly it can increase the power yield from the wind, alleviate the load peak in the electrical-mechanical drive train, and posses a long life time, also, it can offer the possibility to store the briefly timely wind-conditioned power fluctuations in the wind rotor, in which the rotary masses are used as storages of kinetic energy, consequently, the variable speed wind turbines are utilized in the wind power industry widely. In this work, on the basis of a planetary transmission a new kind of drive train for the variable speed wind turbines is proposed. The new drive train consists of wind rotor, three-shafted planetary gear set, generator and Servo Motor. The wind rotor is coupled with the planet carrier of the planetary transmission, the generator is connected with the ring gear through an adjustment gear pair, and the Servo Motor is fixed to the sun gear. By controlling the electromagnetic torque or speed of the Servo Motor, the variable speed operation of the wind rotor and the constant speed operation of the generator are realized, therefore, the generator can be coupled with the grid directly. At the nominal operation point, about 80% of the rotor power flow through the generator directly and 20% through the Servo Motor and a small power electronics system into the grid. As a result, the disadvantages in the traditional wind turbines, e.g. high price of power electronics system, much power loss, strong reaction from the grid and large crash load in the drive train will be avoided.
Hongpong Chen - One of the best experts on this subject based on the ideXlab platform.
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a pm synchronous Servo Motor drive with an on line trained fuzzy neural network controller
IEEE Transactions on Energy Conversion, 1998Co-Authors: Faajeng Lin, Rong-jong Wai, Hongpong ChenAbstract:A permanent magnet (PM) synchronous Servo Motor drive with integral-proportional (IP) position controller and a proposed on-line trained fuzzy neural network (FNN) controller is introduced in this paper. First, an IP position controller is designed according to the estimated plant model to match the time-domain command tracking specifications. Then the resulting closed-loop tracking transfer function is used as the reference model, and an adaptive signal generated from the proposed FNN controller, whose membership functions and connective weights are trained on-line according to the model-following error of the states, is added to the control system to preserve a favorable model-following characteristics under various operating conditions.
Kuangwei Lin - One of the best experts on this subject based on the ideXlab platform.
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automatic control loop tuning for permanent magnet ac Servo Motor drives
IEEE Transactions on Industrial Electronics, 2016Co-Authors: Shengming Yang, Kuangwei LinAbstract:Servo Motor drives generally consist of current, velocity, and position control loops. Tuning these controllers to achieve satisfactory and consistent dynamic responses is crucial. In this paper, a parameter identification and autotuning scheme for permanent-magnet ac Servo Motor drives is presented. Motor electrical parameters such as resistance and inductances were identified first for current control loop tuning. The torque constant and mechanical parameters were then identified for velocity and position loop tuning. The experimental results verified that the proposed scheme can estimate parameters accurately and within a short time. In addition, the system tuned by the proposed scheme was consistent with the desired dynamic performance.
