• Journal of Electrical Engineering and Technology
• /
• v.10 no.2
• /
• pp.529-538
• /
• 2015

Due to the high efficiency and compact mechanical structure, direct drive variable speed generators are used for power conversion in wind turbines. The wind energy conversion system (WECS) considered in this paper consists of a permanent magnet synchronous generator (PMSG), uncontrolled rectifier, dc-dc boost converter controlled with maximum power point tracking (MPPT) and adaptive hysteresis controlled voltage source inverter (VSI). For high utilization of the converter's power capability and stabilizing voltage and power flow, constant DC-link voltage is essential. Step and search MPPT algorithm which senses the rectified voltage ($V_{DC}$) alone and controls the same is used to effectively maximize the output power. The adaptive hysteresis band current control is characterized by fast dynamic response and constant switching frequency. With MPPT and adaptive hysteresis band current control in VSI, the DC link voltage is maintained constant under variable wind speeds and transient grid currents respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.199-203
• /
• 1997

In this paper is proposed a new direct adaptive fuzzy controller that dan ve applied for tracking control of a class of uncertain nonlinear SISO systems. It is shown that, in the presence of the perturbations such as fuzzy approximation error and external disturbance, boundedness of all the signals in the system is ensured, while under the assumption of no perturbations, the stability of the overall system in guaranteed. Also, the concept of persistent excitation in the adaptive fuzzy control systems is introduced to guarantee the convergence and the boundedness of adaptation parameter in the proposed controllers. Simulation example shows the effectiveness of the proposed method in the presence of fuzzy approximation error and external disturbance.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.5
• /
• pp.315-322
• /
• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1730-1731
• /
• 2007

In this paper, we present a direct adaptive control method using neural networks for the control of nonlinear systems. The weights of neural networks are trained by an adaptive backpropagation algorithm based on Lyapunov stability theory. We develop the parameter update-laws using the neural network input and the error between the desired output and the output of nonlinear plant to update the weights of a neural network in the sense that Lyapunove stability theory. Beside the output tracking error is asymptotically converged to zero.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.100-104
• /
• 1998

This paper describes the real-time implementation of an adaptive controller fur the robotic manipulator. Digital signal processors(DSPs) are special purpose micro-processors that are particularly powerful for intensive numerical computations involving sums and products of variables. TMS320C50 chips are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the direct adaptive control theory. The adaptive controller consists of an adaptive feedforward controller and feedback controller. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a assembling robot.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.3
• /
• pp.311-319
• /
• 1992

In this paper, a direct adaptive pole placement controller for an unknown linear time-invariant single-input single-output nonminimum phase plant is proposed. To design this direct adaptive pole placement controller, the auxiliary signals are introduced. Consequently, a linear equation error model is formulated for estimating both the controller parameters and the additional auxiliary parameters. To estimate the controller parameters and the additional auxiliary parameters, the exponentially weighted least-squares algorithm is implemented, and a method of selecting the characteristic polynomials of the sensitivity function filters is proposed. In this method, all the past measurement data are weighted exponentially. A series of simulations for a nonminimum phase plant is presented to illustrate some features of both the parameter estimation and the output response of this adaptive pole placement controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.05a
• /
• pp.370-374
• /
• 1999

The proposed algorithm used the Hybrid teaming rule in the input and hidden layer, and Back-Propagation teaming rule in the hidden and output layer. From the results of simulation of tracking control with one link manipulator as a plant, we verify the usefulness of the proposed control method to compare with common direct adaptive neural network control method; proposed hybrid teaming rule showed faster loaming time faster settling time than the direct adaptive neural network using Back-propagation algorithm. Usefulness of the proposed control method is that it is faster the learning time and settling time than common direct adaptive neural network control method.

• Journal of Ocean Engineering and Technology
• /
• v.3 no.2
• /
• pp.559-559
• /
• 1989

This paper deals with the robust controller design of robot manipulator to track a desired trajectory in spite of the presence of unmodelled dynamics in cause of nonlinearity and parameter uncertainty. The approach follwed in this paper is based on model reference adaptive control technique and convergence on hyperstability theory but it does away with the assumption that process is characterized by a linear model remaining time invariant during adaptation process. The performance of controller is demonstrated by computed simulation about position and speed control of six link manipulator in case of disturbance and payload variation.

• Journal of Ocean Engineering and Technology
• /
• v.3 no.2
• /
• pp.59-69
• /
• 1989

This paper deals with the robust controller design of robot manipulator to track a desired trajectory in spite of the presence of unmodelled dynamics in cause of nonlinearity and parameter uncertainty. The approach follwed in this paper is based on model reference adaptive control technique and convergence on hyperstability theory but it does away with the assumption that process is characterized by a linear model remaining time invariant during adaptation process. The performance of controller is demonstrated by computed simulation about position and speed control of six link manipulator in case of disturbance and payload variation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.48.3-48
• /
• 2002

1) Linear state feedback control design problem for plant with unknown deterministic disturbance is considered and a method to realize state feedback by using adaptive observer which estimates the unknown disturbance simultaneously is proposed. 2) From the viewpoint of practical application, we propose an extended adaptive observer with direct plant path from input to output, which is necessary to use the acceleration type sensors as plant output. 3) Theoretical result is confirmed by numerical simulation of 1-DOF vibration control system.