• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.274-279
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• 2000

Driving of the engine makes unbalance forces which induces vibration to the engine mount system. Active vibration control must be performed to reduce the vibration and the propagation of structure-born sound. In this study, the engine system is modeled as 3-dim. vibration system including flexible structures and an effective active noise control method is proposed. Also, appropriate actuator and sensor locations and types are selected. The miniature of the engine vibration system with multi-input multi-output is built and an active vibration control with multiple filtered-X LMS algorithm is applied to it. The applied control method was effective to reduce the transmitted vibration power through the rubber mount It showed the feasibility of the control of the engine vibration systems with flexible structures.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.342-344
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• 2006

The modem enormous electric power system has made power system analysis much more complex and difficult. For effective analysis of the power system, model reduction and aggregation is required. In this paper, a new aggregation method is presented to aggregate the coherent generators in the large scale power system while matching the power flow. In order to demonstrate the effects of this aggregation method, it is applied to a small scale power system. A multi-variable control technique of $H_{\infty}$ control is also applied to enhance the dynamic stability of the aggregated power system.

• International Journal of Aeronautical and Space Sciences
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• 제12권2호
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• pp.179-189
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• 2011

In this paper, robust adaptive control design problem is addressed for a class of parametrically uncertain aeroelastic systems. A full-state robust adaptive controller was designed to suppress aeroelastic vibrations of a nonlinear wing section. The design used leading and trailing edge control actuations. The full state feedback (FSFB) control yielded a global uniformly ultimately bounded result for two-axis vibration suppression. The pitching and plunging displacements were measurable; however, the pitching and plunging rates were not measurable. Thus, a high gain observer was used to modify the FSFB control design to become an output feedback (OFB) design while the stability analysis for the OFB control law was presented. Simulation results demonstrate the efficacy of the multi-input multi-output control toward suppressing aeroelastic vibrations and limit cycle oscillations occurring in pre- and post-flutter velocity regimes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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• pp.446-449
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• 1990

A Multi-Robot Control language (MRCL) is proposed to effectively control the multi-robot. MRCL has not only single-robot, command, but multi-robot command with multi-task OS, XINU. Concurrent motion, coordinate motion, and simple collision avoidance motion are implemented. This language is expected to act as a intelligent supporting tool for multi-robot system. To verify the effectiveness of the MRCL, a simple puzzle matching example is illustrated.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권11호
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• pp.591-598
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• 2000

In this thesis, a digital tracking controller is proposed for multi-axis position control system. Tracking and contouring error exist when the machine tool moves along a trajectory in multi-axis system. The proposed scheme enhances the tracking and contouring performance by reducing the errors. Also, an optimal tracking controller reduces the tracking error by the state feedback and the feedforward compensator reduces the effects of a nonlinear disturbance such as friction or dead zone. The proposed control scheme reduces the contour error which occurred when the tool tracks the reference trajectory. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real XY servo system.

• 드라이브 ㆍ 컨트롤
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• 제14권2호
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.59.5-59
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• 2001

Multi-agent robot system is the system which executes by cooperating with each robots and controlling several robots. Capability and function of each robot must be considered for cooperation behavior. Furthermore, it is necessary to analyze the given environment and to replace complex task with some simple tasks. Analysis of the given environment and role assignment for the given tasks are composed of discret event. In this paper, the hierarchical controller for multi-agent robot system using the petri-net state diagram is proposed. The proposed modeling method is implemented for soccer robot system. The effectiveness of proposed modeling method is shown through experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2023-2028
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• 2004

This paper reveals the utilization of the multi-gent system that based on the Blackboard system basis as the controller of Soccer Robot. This system is a portion of developing the Soccer Robot team for Robocup 2004 Competition. In this development, the intelligent control system was initiated by the combination of parallel and distributed blackboard structures with the principle design that generated from human body structures, which consists of the combination of two main systems, the organs system and the brain system. The system is designed using the control system theory based on Blackboard basis. Modification of the initial structures to corroborate the Soccer Robot and the structure's constituents are clarified accordingly. To demonstrate the idea, ITE-old team is given as a case study.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.187-196
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• 1997

This paper presents a semi-automatic methodology to synthesize executable digital controller saftware in a multi-loop control system. A digital controller is described by a task graph and end-to-end timing requirements. A task graph denotes the software structure of the controller, and the end-to-end requirements establish timing relationships between external inputs and outputs. Our approach translates the end-to-end requirements into a set of task attributes such as task periods and deadlines using nonlinear optimization techniques. Such attributes are essential for control engineers to implement control programs and schedule them in a control system with limited resources. In current engineering practice, human programmers manually derive those attributes in an ad hoc manner: they often resort to radical over-sampling to safely guarantee the given timing requirements, and thus render the resultant system poorly utilized. After task-specific attributes are derived, the tasks are scheduled on a single CPU and the compiled kernel is synthesized. We illustrate this process with a non-trivial servo motor control system.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(2)
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• pp.584-587
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• 2003

Iterative learning control is an approach to improve the transient response of systems that operate repetitively over a fixed time interval. It is useful for the system where the system output follows the different type input, in case of design or modeling uncertainty In this paper, we introduce the concept of iterative learning control and then apply the learning control algorithm for multi-motor system for performance Improvement.