• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.87-93
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• 2012

In this paper, a formation guidance method for UAVs (Unmanned Aerial Vehicles) to simulate the formation flight of birds proposed. The proposed method solves all issues of approaching for formation, formation keeping, and scarce chance to be collided with each UAV during formation process. Also, we design the feedforward controller to compensate the change of speed and heading for maneuvering of the leader UAV and the feedback controller to consider the response lag of the system. The stability and performance of the proposed controller is verified via numerical simulations of the full 6-Dof model of UAV.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.2
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• pp.182-192
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• 2015

This study develops a digital control scheme with power factor correction for a front-end converter in an electric vehicle battery charger. The front-end converter acts as the boost-type switching-mode rectifier. The converter assumes the two roles of the battery charger, which include power factor control and robust charging performance. The proposed control scheme consists of a charging control algorithm and a grid current control algorithm. The scheme aims to obtain unity input power factor and robust performance. Based on the linear average model of the converter, a constant-current constant-voltage charging control algorithm that passes through only one proportional-integral controller and a current feed-forward path is proposed. In the current control algorithm, we utilized a second band pass filter, a single-phase phase-locked loop technique, and a duty-ratio feed-forward term to control the grid current to be in phase with the grid voltage and achieve pure sinusoidal waveform. Simulations and experiments were conducted to verify the effectiveness of the proposed control scheme, both simulations and experiments.

• Journal of Power Electronics
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• v.16 no.1
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• pp.249-258
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• 2016

Given that elastic connection is often used between motor drives and load devices in industrial applications, vibration often occurs at the load side. Vibration suppression is a crucial problem that needs to be addressed to achieve a high-performance servo-control system. Scholars have presented many strategies to suppress vibration. In this study, we propose a method to diminish vibration by using a torque feed-forward and disturbance torque observer. We analyze the system performance and explain the principle of the proposed vibration suppression method based on the transfer functions of the system. The design of controller parameters is another important issue in practical applications. We accordingly provide a succinct outline of the design specifications based on the coefficient diagram method. Furthermore, we build a model under the Simulink environment and conduct experiments to validate the proposed method. Results show that speed and position vibrations are successfully suppressed by the proposed method.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.771-776
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• 1991

In this paper. an indirect adaptive controller for manipulator which is composed of two controller structure is considered. One is feedforward controller in which the dynamics equation solved and the other is feedback controller in which the output error compensated. This controller has a good performance, but the computation burden of the feed forward controller keep from real time control. At this point, we proposed the two time adaptive controller where the sampling time of the feedforward controller is quite longer than that of the feedback controller. By the computer simulation, this proposed two time adaptive controller shows good performance in the view of accuracy in spite of decreasing computational burden.

• Smart Structures and Systems
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• v.3 no.2
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• pp.147-172
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• 2007

The present paper is concerned with the design of distributed sensors and actuators. Strain type sensors and actuators are considered with their intensity continuously distributed throughout a continuous structure. The sensors measure a weighted average of the strain tensor. As a starting point for their design we introduce the concept of collocated sensors and actuators as well as the so-called natural output. Then we utilize the principle of virtual work for an auxiliary quasi-static problem to assign a mechanical interpretation to the natural output of the sensors to be designed. Therefore, we take the virtual displacements in the principle of virtual work as that part of the displacement in the original problem, which characterizes the deviation from a desired one. We introduce different kinds of distributed sensors, each of them with a mechanical interpretation other than a weighted average of the strain tensor. Additionally, we assign a mechanical interpretation to the collocated actuators as well; for that purpose we use an extended body force analogy. The sensors and actuators are applied to solve the displacement tracking problem for continuous structures; i.e., the problem of enforcing a desired displacement field. We discuss feed forward and feed back control. In the case of feed back control we show that a PD controller can stabilize the continuous system. Finally, a numerical example is presented. A desired deflection of a clamped-clamped beam is tracked by means of feed forward control, feed back control and a combination of the two.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.112-118
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• 2000

A modified repetitive control is formulated and analyzed in the discrete-time domain. Sufficient conditions for the stability of a class of repetitive controllers are given by means of the regeneration spectrum method. When a periodic signal input is drived into the two-mass-spring plant, the performance of the proposed controller which comprises a low-pass filter and two feed-forward compensators, turns out highly accurate by comparing the tracking result from the conventional LQ controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.82-86
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• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1088-1092
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• 2003

This paper presents a combined lookup table technique and PI-type controller. The purpose of the designed controller is applied to control the nonlinear system as thermal process. The proposed controller is easy and convenient to design based on a commercial controller. The performances of the proposed controller were studied using the thermal plant model under temperature control. The experimental results included demonstrate the good performance of the proposed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• Journal of Industrial Technology
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• v.18
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• pp.303-308
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• 1998

In this paper a neural network controller called "Feedback-State Learning" for control of the attitude of a wheeled inverted pendulum is presented. For the controller the design of a stable feedback controller is necessary, so the LQR is used for the feedback controller because the LQR has good performance on controlling nonlinear systems. And the neural networks are used for a feed forward controller. The designed controller is applied to the stabilization of a wheeled inverted pendulum. Because of its nonlinear characteristics such as friction and parameter variations in the linearization, the wheeled inverted pendulum is used for demonstration of the effectiveness of the proposed controller.