• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.331-336
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• 1989

Under the condition of stable inverse a billinear model predictive control method for SISO and MIMO system with time delay is derived. For processes subject to a bounded disturbance the proposed control method with a classical recursive adaptation algorithm was shown to be stable in the sense of the convergence of parameter estimates and the boundedness of the control error. Several simulation results demonstrate the characteristics of the proposed bilinear model predictive control method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.736-741
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• 1992

The Stewart platform is one example of a motion simulator which generates 6 DOF motion in space by 6 actuators connected in parallel. The present SISO controllers are designed to track displacement command of each actuator computed from reference 6 DOF motion of platform by Stewart platform inverse kinematics. But this type of control can't cope with external load variation, geometric configuration of motion simulator, and different dynamic behavior of 6 DOF motion. In this paper, a multivariable controller using H- optimal control theory is designed for linerized simulator model with each actuator driving force as control input and platform 6 DOF motion as measured output. Nonlinear simulation result of the H$_{\infty}$ MIMO controller is not satisfied in steady-state characteristics. But the proposed H$_{\infty}$ + PI control scheme shows acceptable performance.e.e.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.445-445
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• 2000

This paper proposes the MIMO indirect adaptive fuzzy controller to control the two-link manipulators. The input-output linearization technique, equivalent control input plus integral term, augmented error model and recursive least square adaptive law are used fer the controller. The linear type of fuzzifier-defuzzifier fuzzy logic system used for nonlinear function makes easy to farm the error model and able to follow the adaptive system approach. Such that control approach, the control system is not required joint speed and accerelation measurement and easy to implement and tune. The simulation results showed that the proposed controller has good control performance, stability, very small tracking error, decoupling, fast convergence, robust to parameter variation and load.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2188-2191
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• 2002

MIMO 비최소위상 시스템에 대한 입출력 선형화 제어에 대해서 새로운 접근 방식을 제안한다. 처음에 몇가지 조건 하에서 비선형 궤환과 상태 변환을 하고 또한 magnitude & time scaling을 해서 일반적인 비선형 시스템을 특이 섭동 시스템으로 변환할 수 있다는 것을 보였다. 특히 제안된 방법에 의하여 변환된 특이 섭동 시스템에서 숨겨진 동적 특성이 fast subsystem의 역할을 하게 된다. 그 다음에는 잘 알려진 composite control 기법을 적용하여 시스템이 거의 선형적이고 비간섭적인 I/O 동적 특성을 갖게 하고 내부 상태가 안정화되도록 한다. 기존의 방식 보다 제안된 제어 방법의 가장 큰 이점은 적용될 수 있는 비최소위상 시스템의 범위를 보다 넓히게 되었다는 것이다. 게다가 특이 섭동 방법은 제어기 설계 과정을 단순화시켜 제어기 구현에 있어서 계산 시간을 단축시킨다.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.191-196
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• 1993

Since the welding process is complex and highly nonlinear, it is very difficult to accurately model the process for real-time control. In this paper, a discrete-time transfer function matrix model for gas metal arc welding process is proposed. Although this linearized model is valid only around the operating point of interest, the adaptation mechanism employed in the control system render this model useful over a wide operating range. A multivariable one-step-ahead adaptive control strategy combined with a recursive least-squares method for on-line parameter estimation is implemented in order to achieve the desired weld bead geometries. Command following and disturbance rejection properties of the adaptive control system for both SISO and MIMO cases are investigated by simulation and experiment.

• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.1-7
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• 2003

Autonomous underwater vehicles (AUVs) are unmanned, underwater vessels that are used to investigate sea environments in the study of oceanography. Docking systems are required to increase the capability of the AUVs, to recharge the batteries, and to transmit data in real time for specific underwater works, such as repented jobs at sea bed. This paper presents a visual :em control system used to dock an AUV into an underwater station. A camera mounted at the now center of the AUV is used to guide the AUV into dock. To create the visual servo control system, this paper derives an optical flow model of a camera, where the projected motions of the image plane are described with the rotational and translational velocities of the AUV. This paper combines the optical flow equation of the camera with the AUVs equation of motion, and deriver a state equation for the visual servo AUV. Further, this paper proposes a discrete-time MIMO controller, minimizing a cost function. The control inputs of the AUV are automatically generated with the projected target position on the CCD plane of the camera and with the AUVs motion. To demonstrate the effectiveness of the modeling and the control law of the visual servo AUV simulations on docking the AUV to a target station are performed with the 6-dof nonlinear equations of REMUS AUV and a CCD camera.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.142-148
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• 2002

Autonomous underwater vehicles (AUVs) are unmanned underwater vessels to investigate sea environments, oceanography and deep-sea resources autonomously. Docking systems are required to increase the capability of the AUVs to recharge the batteries and to transmit data in real time for specific underwater works, such as repeated jobs at sea bed. This paper presents a visual servo control system for an AUV to dock into an underwater station with a camera mounted at the nose center of the AUV. To make the visual servo control system, this paper derives an optical flow model of a camera, where the projected motions of the image plane are described with the rotational and translational velocities of the AUV. This paper combines the optical flow equation of the camera with the AUVs equation of motion, and derives a state equation for the visual servoing AUV. This paper proposes a discrete-time MIMO controller minimizing a cost function. The control inputs of the AUV are automatically generated with the projected target position on the CCD plane of the camera and with the AUVs motion. To demonstrate the effectiveness of the modeling and the control law of the visual servoing AUV, simulations on docking the AUV to a target station are performed with the 6-dof nonlinear equations of REMUS AUV and a CCD camera.