• Smart Structures and Systems
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• 제29권4호
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.378-384
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• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1983년도 하계학술회의강연.논문초록집
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• pp.135-138
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• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.2-2
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• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.573-578
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• 2002

In this paper, it Is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-negro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.122-127
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• 2001

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.256-261
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• 2002

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• 제어로봇시스템학회논문지
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• 제8권9호
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• pp.728-735
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• 2002

The Field robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this study, to field-robotize a hydraulic excavator that is mostly used in construction working, we have developed an automatic excavation system and an adaptive control system. A model-reference adaptive controller has been designed based on the model that is obtained through off-line system identification. It is illustrated by computer simulations that the proposed control system gives good performance in the trajectory tracking control and the adaptation to parameter variation.

• Transactions on Control, Automation and Systems Engineering
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• 제1권1호
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• pp.32-43
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• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• 대한조선학회논문집
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• 제31권2호
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• pp.38-44
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• 1994

1960년대 Auto-Pilot 시스템이 대양을 항해하는 선박에 장착되면서 운항경제성 및 선원 승선감의 견지에서 Auto-Pilot시스템의 제어 알고리듬이 연구되기 시작하였다. 초기에는 PD제어로 시작하였으나 잦은 타동작으로 인한 기구 마모를 줄이기 위해 실제 선수각과 설정선수방위 차가 어느 상한치 이상에서만 타각을 조작하는 on-off 제어를 도입하였다. 본 논문에서는 Auto-Pilot 시스템의 제어 알고리듬에 optimal제어, adaptive제어 등을 적용하여 제어기법간의 비교를 cost function을 통하여 수행함으로써 Auto-Pilot 시스템에 대한 최적의 제어기법을 조사하였다. Adaptive 제어를 위한 선박 조종운동방정식의 parameterization 과정을 검토하였고 adaptive 알고리듬의 장점이 파라미터 추정이 잘못된 경우의 수치시뮬레이션 결과로부터 분명히 알 수 있었다.